Non-Overlapping Conditions to Enable Multi- Dimensional Behavioral Models/DPDs for Multi-Band or Non-Continuous Carrier Aggregation Systems

To linearize the multi.band PAs/transmitters, a serial of multi.band predistortion models based on multi.dimensional architecture have been proposed. However, most of these models work properly only for the signals whose harmonic and intermodulation products of carriers' non.overlap with the interested fundamental bands. In this paper, the non.overlapping conditions for dual.band and tri.band signals are derived and denoted in the form of closed.form expression. It can be used to verify whether a given dual.band/multi.band signals can be linearized properly by these multi.dimensional behavioral models. Also the conditions can be used to plan the frequency spacing and maximum bandwidth of a multi.band or non.continuous carrier aggregation signal. Several dual.band and triband signals were tested on the same PA, by employing 2.D DPD and 3.D DPD behavioral models. The measurement results show that the signals which don't satisfy the non.overlapping conditions cannot be linearized well by the multi.dimensional behavioral models which does not take the harmonic and intermodulation products of carriers' into account.

ANIMAL BEHAVIORAL MODELS OF TINNITUS

The pathophysiology of tinnitus is poorly understood and treatments are often unsuccessful. A number of animal models have been developed in order to gain a better understanding of tinnitus. A great deal has been learned from these models re- garding the electrophysiological and neuroanatomical correlates of tinnitus following exposure to noise or ototoxic drugs. Re- liable behavioral data is important for determining whether such electrophysiological or neuroanatomical changes are indeed related to tinnitus. Of the many documented tinnitus animal behavioral paradigms, the acoustic startle reflex had been pro- posed as a simple method to identify the presence or absence of tinnitus. Several behavioral models based on conditioned re- sponse suppression paradigms have also been developed. In addition to determining the presence or absence of tinnitus, some of the behavioral paradigms have provided signs of the onset, frequency, and intensity of tinnitus in animals. Although none of these behavioral models have been proved to be a perfect model, these studies provide useful information on understanding the neural mechanisms underlying tinnitus.

Multislice behavioral modeling based on envelope domain for power amplifiers

An envelope domain multislice behavioral modeling is introduced. The tradition AM-AM and AM- PM characteristics of power amplifiers axe extended to envelope domain and base-band filter is applied to distortion complex envelope signal for description of the envelope memory effect. Using traditional one and two-tone tests, the coefficients of nonlinear model and the FIR filter can be extracted. At last the model has been applied to a 10 W WCDMA Power amplifier to predict its output signal. And simulation results show that the model output conforms very well to the traditional transistor level simulation results.

Deep Neural Network Based Behavioral Model of Nonlinear Circuits

With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.

Behavioral Model of Molecular Gap-Type Atomic Switches and Its SPICE Integration

Atomic switches can be used in future nanodevices and to realize conceptually novel electronics in new types of computer architecture because of their simple structure, ease of operation, stability, and reliability. The atomic switch is a single solid-state switch with inherent learning abilities that exhibits various nonlinear behaviors with network devices. However, previous studies focused on experiments and nonvolatile memory applications, and studies on the application of the physical properties of the atomic switch in computing were nonexistent. Therefore, we present a simple behavioral model of a molecular gap-type atomic switch that can be included in a simulator. The model was described by three simple equations that reproduced the bistability using a double-well potential and was able to easily be transferred to a simulator using arbitrary numerical values and be integrated into HSPICE. Simulations using the experimental parameters of the proposed atomic switch agreed with the experimental results. This model will allow circuit designers to explore new architectures, contributing to the development of new computing methods.

An Improved Behavioral Model for High-voltage and High-power IGBT Chips

High-voltage and high-power IGBT chips have a noticeable carrier storage effect,which is related to the load current.However,the research on the carrier storage effect of existing IGBT behavior models is insufficient.In this paper,An improved behavioral model for high-voltage and high-power insulated gate bipolar transistor(IGBT)chips is proposed,which could be used under different load conditions.The problems for applying the traditional behavioral model to more load conditions are discussed.Carrier behavior,in the wide base region,is analyzed,and the analytical expression of the carrierstorage-effect equivalent capacitance and the initial value of the tail current are provided to establish an improved IGBT behavioral model.A corresponding parameter extraction method is proposed.In order to verify the improved behavioral model,an experimental platform is built for resistive load and inductive load,and the results show that the accuracy of the improved behavioral model is much better than that of the traditional model.In addition,the errors of the improved model are within 12.5%under different current and load types.Considering that the maximum error of other models,which could be applied in a variety of load conditions,is more than 25%,the accuracy of the model proposed in this paper is excellent.

Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

Simulink Behavioral Modeling of a 10-bit Pipelined ADC

The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters （ADCs）. All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters （white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages）. Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.

Behavioral Model of Decision-Making in Economic Systems

A behavioral model of decision-making is presented to obtain the optimal solution of some economic systems. A numerical example is discussed in detail with what-if and what-for analysis to illustrate the advantages of this model.

An Envelope Hammerstein Model for Power Amplifiers

In this paper, an envelope Hammerstein （EH） model is introduced to describe dynamic input -output characteristics of RF power amplifiers. In the modeling approach, we use a new truncation method and an established nonlinear time series method to determine model structure. Then, we discuss the process of model parameter extraction in detailed. Finally, a 2 W WCDMA power amplifier is measured to verify the performance of EH model, and good agreement between model output and measurement result shows our model can accurately predict output characteristic of the power amplifier.

Symbolic Macromodeling for Statistical Simulation of Operational Amplifiers

Symbolic circuit simulator is traditionally applied to the small-signal analysis of analog circuits. This paper establishes a symbolic behavioral macromodeling method applicable to both small-signal and large-signal analysis of general two-stage operational amplifiers （op-amps）. The proposed method creates a two-pole parametric macromodel whose parameters are analytical functions of the circuit element parameters generated by a symbolic circuit simulator. A moment matching technique is used in deriving the analytical model parameter. The created parametric behavioral model can be used for op-amps performance simulation in both frequency and time domains. In particular, the parametric models are highly suited for fast statistical simulation of op-amps in the time-domain. Experiment results show that the statistical distributions of the op-amp slew and settling time characterized by the proposed model agree well with the transistor-level results in addition to achieving significant speedup.

GLOBAL EXISTENCE AND ASYMPTOTIC BEHAVIOR FOR AN 1-D COMPRESSIBLE ENERGY TRANSPORT MODEL

In this article, the global existence and the large time behavior of smooth solutions to the initial boundary value problem for a degenerate compressible energy transport model are established.

High-temperature Creep Behavior Characterization of Asphalt Mixture based on Micromechanical Modeling and Virtual Test

The high-temperature creep behavior of asphalt mixture was investigated based on micromechanical modeling and virtual test by using three-dimensional discrete element method（DEM）. A user-defined micromechanical model of asphalt mixture was established after analyzing the irregular shape and gradation of coarse aggregates, the viscoelastic property of asphalt mastic, and the random distribution of air voids within the asphalt mixture. Virtual uniaxial static creep test at 60 ℃ was conducted by using Particle Flow Code in three dimensions（PFC3D） and was validated by laboratory test. Based on virtual creep test, the micromechanical characteristics between aggregates, within asphalt mastic, and between aggregate and asphalt mastic were analyzed for the asphalt mixture. It is proved that the virtual test based on the micromechanical model can efficiently predict the creep deformation of asphalt mixture. And the high-temperature behavior of asphalt mixture was characterized from micromechanical perspective.

Switching mechanism for TiO_2 memristor and quantitative analysis of exponential model parameters

The memristor, as the fourth basic circuit element, has drawn worldwide attention since its physical implementation was released by HP Labs in 2008. However, at the nano-scale, there are many difficulties for memristor physical realization. So a better understanding and analysis of a good model will help us to study the characteristics of a memristor. In this paper, we analyze a possible mechanism for the switching behavior of a memristor with a Pt/TiO2/Pt structure, and explain the changes of electronic barrier at the interface of Pt/TiO2. Then, a quantitative analysis about each parameter in the exponential model of memristor is conducted based on the calculation results. The analysis results are validated by simulation results. The efforts made in this paper will provide researchers with theoretical guidance on choosing appropriate values for(α, β, χ, γ) in this exponential model.

Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent learning.Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process.This digital learning improves the quality of teaching and also promotes educational equity.However,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning environment.The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy.It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course.It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level.In this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment.Catering to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm.An adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Dynamic Behavior Modeling in Multi-Agent System By Evolutionary Programming

In a multi-agent system, each agent must adapt itself to the environment and coordinate with other agents dynamically. TO predict or cooperate with the behavior of oiller agents. An agent should dynamically establish and evolve the cooperative behavior model of itself. In this paper, we represent the behavior model of an agent as a f-mite state machine and propose a new method of dynamically evolving the behavior model of an agent by evolutionary programming.

Constitutive modeling for mechanical behaviors of geomaterials, newdesigns and techniques in geotechnical engineering

This Special Issue of the Journal of Rock Mechanics and GeotechnicalEngineering （JRMGE） contains 13 papers prepared by internationalexperts on various general topics in geomechanics, rockmechanics and geotechnical engineering. It represents a usefulmix of theoretical developments, testing and practical applications.We present in the following brief details in the papers, alphabeticallyin accordance with the last name of the first author.Barla presents a review of tunneling techniques with emphasison the full-face method combining full-face excavation and facereinforcement by means of fiber-glass elements with a yieldcontrolsupport. This method has been used successfully in difficultgeologic conditions, and for a wide spectrum of ground situations.The validation of the method with respect to the Saint Martin LaPorte access adit along the LyoneTurin Base tunnel experiencingseverely squeezing conditions during excavation is also includedin the paper. The numerical modeling with consideration of therock mass time-dependent behavior showed a satisfactory agreementwith monitoring results.

Design of Simulation Competition Platform Based on Cognitive Behavior Modeling

Cognitive behavior modeling of agent is an important component of simulation system,and there are some difficulties in the simulation of course teaching.When students make simulation experiments about cognitive behavior modeling,such as algorithm design and model construction,there is no simulation competition platform that is controllable,flexible and scalable.To solve this problem,we propose a simulation competition platform based on cognitive behavior modeling,called TankSim,for undergraduate and graduate students.This platform aims to cultivate studenfs team collaboration and innovation capability,and improve their learning motivation.This paper elaborates the proposed platform from three aspects,including demand analysis,platform design,and content design.

老年患者门诊预约挂号的影响因素:基于安德森健康行为模型的实证研究

目的基于安德森健康行为模型,研究老年患者门诊预约挂号的影响因素,为优化门诊预约挂号服务、推进老年患者预约挂号提供参考。方法以安德森健康行为模型为理论框架设计问卷,采用方便抽样法向上海某三级甲等综合医院门诊老年患者发放调查问卷。将各维度因素纳入二分类logistic回归模型,采用单因素分析和logistic回归分析探讨老年患者门诊预约挂号的影响因素。结果共回收282份有效问卷,预约挂号187人,占66.31%。曾使用过1~2种预约挂号服务、存在社会支持、距离医院路程80 min以上、收入为>5000~7500元、就诊科室预约率25.00%以上、有预约挂号使用意愿的老年患者更倾向于预约挂号。患慢性病数量在5种及以上的老年患者更不倾向于预约挂号。结论老年患者门诊预约需求较大且受多种因素影响。须关注老年人预约挂号“痛点”,关怀老年群体,共建支持网络,加强有效宣传,优化医疗资源配置,激发使用意愿。