A DISCRETE TIME TWO-LEVEL MIXED SERVICE PARALLEL POLLING MODEL

We present a discrete time single-server two-level mixed service polling systems with two queue types, one center queue and N normal queues. Two-level means the center queue will be successive served after each normal queue. In the first level, server visits between the center queue and the normal queue. In the second level, normal queues are polled by a cyclic order. Mixed service means the service discipline are exhaustive for center queue, and parallel 1-limited for normal queues. We propose an imbedded Markov chain framework to drive the closed-form expressions for the mean cycle time, mean queue length, and mean waiting time. Numerical examples demonstrate that theoretical and simulation results are identical the new system efficiently differentiates priorities.

Analytic Solution of a Two-Level Model Coupled by Y_(5,μ)Field

An analytic solution of a two-level model coupled by Y5μ field was given inthe limit of large angular momentum 11.

Symmetry of Y_5 Deformation and Two-Level Model

The symmetry of Y5μ-deformed fields are classified and the one-particlespectra in two-level model coupled by Y5μ fields are discussed.

Dissipative quantum phase transition in a biased Tavis-Cummings model

We study the dissipative quantum phase transition(QPT)in a biased Tavis–Cummings model consisting of an ensemble of two-level systems(TLSs)interacting with a cavity mode,where the TLSs are pumped by a drive field.In our proposal,we use a dissipative TLS ensemble and an active cavity with effective gain.In the weak drive-field limit,the QPT can occur under the combined actions of the loss and gain of the system.Owing to the active cavity,the QPT behavior can be much differentiated even for a finite strength of the drive field on the TLS ensemble.Also,we propose to implement our scheme based on the dissipative nitrogen-vacancy(NV)centers coupled to an active optical cavity made from the gainmedium-doped silica.Furthermore,we show that the QPT can be measured by probing the transmission spectrum of the cavity embedding the ensemble of the NV centers.

Design and Implementation of Two-Level Metadata Server in Small-Scale Cluster File System

The reliability and high performance of metadata service is crucial to the store architecture. A novel design of a two-level metadata server file system （TTMFS） is presented, which behaves high reliability and performance. The merits both centralized management and distributed management are considered simultaneously in our design. In this file system, the advanced-metadata server is responsible for manage directory metadata and the whole namespace. The double-metadata server is responsible for maintaining file metadata. And this paper uses the Markov return model to analyze the reliability of the two-level metadata server. The experiment data indicates that the design can provide high throughput.

Entropy evolution of field with a time-varying frequency in the Jaynes-Cummings model

Following Jaynes-Cummings model,the evolution of the field entropy in the system of a two-level atom interacting with the single mode coherent field is investigated under rotating-wave approximation.The typical case "the field frequency variance with time in the form of sine ω=ω0+usin(wt) has been considered.The influences of the amplitude and angle frequency of the field frequency variance on entropy evolution of the field are discussed by numerical calculations.Calculation results indicate that the field frequency variance influences violently the behavior of field entropy evolution;the larger the amplitude of the field frequency variance is,the stronger the influence of the field frequency variance on the time evolution of field entropy is.

Two-level vehicle path planning model for multi-warehouse robots with conflict solution strategies and improved ACO

With the rapid development of warehouse robots in logistics and other industries,research on their path planning has become increasingly important.Based on the analysis of various conflicts that occur when the warehouse robot travels,this study proposes a two-level vehicle path planning model for multi-warehouse robots,which integrates static and dynamic planning to improve operational efficiency and reduce operating costs.In the static phase,the blockage factor is introduced to enhance the ant colony optimization(ACO)algorithm as a negative feedback mechanism to effectively avoid the blockage nodes during movement.In the dynamic stage,a dynamic priority mechanism is designed to adjust the routing strategy in real time and give the optimal path according to the real situation.To evaluate the model’s effectiveness,simulations were performed under different operating environments and application strategies based on an actual grid environment map.The simulation results confirm that the proposed model outperforms other methods in terms of average running distance,number of blocked nodes,percentage of replanned paths,and average running time,showing great potential in optimizing warehouse operations.

Frequency-modulated excitation of Rydberg potassium atoms by using B-spline

By using the B-spline expansion technique and a model potential of the alkali atoms, the properties of frequency- modulated excitation of Rydberg potassium atoms in a static electric field and a microwave field are investigated by using the time-dependent two-level approach. We successfully reproduce the square wave oscillations in the low frequency, the stair step population oscillations in the intermediate frequency, and the multiphoton transitions in the high frequency with respect to the unmodulated Rabi frequency, which have been observed experimentally by Noel et al. [Phys. Rev. A 58 2265 （1998）]. Furthermore, we also numerically obtain the discretized Rabi oscillations predicted in the Landau Zener accumulation model.

Few-shot Learning for Named Entity Recognition Based on BERT and Two-level Model Fusion

Currently,as a basic task of military document information extraction,Named Entity Recognition(NER)for military documents has received great attention.In 2020,China Conference on Knowledge Graph and Semantic Computing(CCKS)and System Engineering Research Institute of Academy of Military Sciences(AMS)issued the NER task for test evaluation,which requires the recognition of four types of entities including Test Elements(TE),Performance Indicators(PI),System Components(SC)and Task Scenarios(TS).Due to the particularity and confidentiality of the military field,only 400 items of annotated data are provided by the organizer.In this paper,the task is regarded as a few-shot learning problem for NER,and a method based on BERT and two-level model fusion is proposed.Firstly,the proposed method is based on several basic models fine tuned by BERT on the training data.Then,a two-level fusion strategy applied to the prediction results of multiple basic models is proposed to alleviate the over-fitting problem.Finally,the labeling errors are eliminated by post-processing.This method achieves F1 score of 0.7203 on the test set of the evaluation task.

Study of Dominant Height for Chinese Fir Plantation Using Two-Level Nonlinear Mixed Effects Model

Nonlinear mixed effects model(NLMEM) is built on the relationship of the fixed and random effects in the regression function.The NLMEM has an obvious comparative advantage in analyzing the longitudinal data,repeated measures data and multilevel data.Two-level NLMEM is used to analyze the dominant height for Chinese fir (Cunninghamia lanceolata).The authors outline the two-level NLMEM and introduce the parameters estimation method of the model.Based on five common Richard and Logistic models,the mixed model is built.The modeling data are used to calculate and compare with 19 models derived from each based model,and 5 optimal mixed models are built.Compared the 5 optimal mixed models with traditional regression models,it is showed that the two-level NLMEM has a better fitting effect than the regression model.

Analysis of Basal Area for Chinese Fir Plantation Using Two Kinds of Nonlinear Mixed Effects Model(Two Levels)

Nonlinear mixed effects model（NLMEM） is based on the relationship between the fixed and random effects in the regression function.The NLMEM has a competitive advantage in analyzing repeated measures data,the longitudinal data and multilevel data.This paper chose two kinds of two-level nonlinear mixed model to analyze basal area growth for Chinese Fir（Cunninghamia lanceolata）. Model 1 is a general two-level NLMEM and Model 2 is based on Model 1 to further consider the fixed effects parameters changes with a specific factor. Firstly,through the analysis of these two models, this paper defined the basic model to build the two-level NLMEM.Secondly,665 kinds of models derived from Model 1 and 2 703 kinds of models derived from Model 2 were calculated and compared. The results showed that:for Model 1,there were 57 kinds of models converging,and when the formal parameter b0 considered the block effects and plot effects,b1 and b4 only considered the block effects, the model fitted the best;and for Model 2,there were 24 kinds of model converging,and when the formal parameter bs considered the block effects and plot effects,b1 only considered block effects and the fixed effects b0 changed with any level of block level, Model 2 fitted the best.Finally,by comparing the traditional nonlinear regression model,Model 1 and Model 2,the results showed that Model 1 and Model 2 fitted better than the traditional nonlinear regression, and Model 2 was best fitting model.

Optimal allocation method of energy storage for integrated renewable generation plants based on power market simulation

This study designs and proposes a method for evaluating the configuration of energy storage for integrated re-newable generation plants in the power spot market,which adopts a two-level optimization model of“system simulation+plant optimization”.The first step is“system simulation”which is using the power market simu-lation model to obtain the initial nodal marginal price and curtailment of the integrated renewable generation plant.The second step is“plant optimization”which is using the operation optimization model of the integrated renewable generation plant to optimize the charge-discharge operation of energy storage.In the third step,“sys-tem simulation”is conducted again,and the combined power of renewable and energy storage inside the plant is brought into the system model and simulated again for 8,760 h of power market year-round to quantify and compare the power generation and revenue of the integrated renewable generation plant after applying energy storage.In the case analysis of the provincial power spot market,an empirical analysis of a 1 GW wind-solar-storage integrated generation plant was conducted.The results show that the economic benefit of energy storage is approximately proportional to its capacity and that there is a slowdown in the growth of economic benefits when the capacity is too large.In the case that the investment benefit of energy storage only considers the in-come of electric energy-related incomes and does not consider the income of capacity mechanism and auxiliary services,the income of energy storage cannot fulfill the economic requirements of energy storage investment.

AGENT based structural static and dynamic collaborative optimization

A static and dynamic collaborative optimization mode for complex machine system and itsontology project relationship are put forward, on which an agent-based structural static and dynamiccollaborative optimization system is constructed as two agent colonies: optimization agent colony andfinite element analysis colony. And a two-level solving strategy as well as the necessity and possibilityfor handing with finite element analysis model in multi-level mode is discussed. Furthermore, the coop-eration of all FEA agents for optimal design of complicated structural is studied in detail. Structural stat-ic and dynamic collaborative optimization of hydraulic excavator working equimpent is taken as an ex-ample to show that the system is reliable.