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.

A function-based behavioral modeling method for air combat simulation

Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is well-suited to tackle such complex states and actions. However, it is not necessary to fuzzify the variables that have definite discrete semantics.Hence, the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchical structures from the perspective of function, namely, the functional decision tree. This method is developed to represent behavioral modeling of air combat systems, and its metamodel,execution mechanism, and code generation can provide a sound basis for function-based behavioral modeling. As a proof of concept, an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.

Nonlinear Auto-Companding Method for Behavioral Modeling of Switched-Current Circuits

A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.

Behavioral modeling of RF power amplifiers with time-delay feed-forward neural networks

A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.

行为建模技术(Behavioral Modeling)在零件设计中的应用

为更好地把握设计意图,在Pro/ENGINEER软件中需要人工创建各种"关系",这种"关系"只能向前引用"尺寸参数",如果需要向后引用"尺寸参数"则要应用行为建模技术。行为建模技术通过建立"分析特征"实现优化目标的建立,以尺寸参数或用户自定义参数为变量对优化目标进行优化。本文通过一个轮胎模型,例证了上述方法的应用过程,得出了优化结果。

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.

Study on Behavior Model in Open Architecture CNC System

Since a CNC controller has different real-time require-ments in difference levels,proper methods for dynamicmodeling must be employed when a CNC controller isdesigned.Based on behavior model in this paper,a newdynamic modeling method is given and used to analyzethe life cycle of application objects and their interactionsin an open architecture CNC controller modeling.Be-sides,the paper develop a solution how to realize recon-figurable structures in CNC systems and seamless con-nection between fuuction modules and system.

Lewin Behavior Model-Based Study on Influence Factors of Individuals to Mobile Service Demand

How to fmd main influence factors of individuals to mobile service demand is investiga- ted. The empirical research is conducted in the sample of high-value customers in China mobile market. Based on Lewin behavior model, this pa- per establishes factors-matrix from personal and environmental dimensions. Relationships among multiple factors are tested in the structural equa- tion model and their impacts on customers＇ de- mands are elaborated. Findings indicate that opera- tional convenience and business brand image have significant effects on sample users＇ demands. Fur- thermore, annual income, gender, occupation, the needs of access to information and the needs of enriching and improving social relationships are al- so important factors for high-value users. The re- suits may provide further insights into mobile service demand and the model can be popularized to other behavior researches.

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.

Hydrate agglomeration modeling and pipeline hydrate slurry flow behavior simulation

Dynamic modeling and numerical simulation of hydrate slurry flow behavior are of great importance to offshore hydrate management.For this purpose, a dynamic model of hydrate agglomeration was proposed in this paper.Based on population balance equation, the frame of the dynamic model was established first, which took both hydrate agglomeration and hydrate breakage into consideration.Then, the calculating methods of four key parameters involved in the dynamic model were given according to hydrate agglomeration dynamics.The four key parameters are collision frequency, agglomeration efficiency, breakage frequency and the size distribution of sub particles resulting from particle breakage.After the whole dynamic model was built, it was combined with several traditional solid–liquid flow models and then together solved by the CFD software FLUENT 14.5.Finally, using this method, the influences of flow rate and hydrate volume fraction on hydrate particle size distribution, hydrate volume concentration distribution and pipeline pressure drop were simulated and analyzed.

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

COMPUTER MODEL OF COPPER SMELTING PROCESS AND DISTRIBUTION BEHAVIORS OF ACCESSORY ELEMENTS

A computer model has been developed to simulate the distribution behaviors of Ni, Co. Sn. Ph,Zn, As, Sb, Bi, An and Ag in copper smelting process. The model assumes that the copper smelting furnaceis in thermodynamic equilibrium. As many as 21 elements (Cu. S, Fe. Ni, Co. Sn, As, Sb. Bi, Ph. Zn.An. Ag. O, N, C, H, Ca, Mg, Al, and St) and 73 compounds are considered. This model accounts forphysical entrainment in the melts. The predictions by the present computer model are compared with theknown commercial data from Guixi Smelter in China, Home Smelter in Canada and Naoshima Smelter inJapan. The agreements between the computer predictions and the commercial data are excellent, so that thepresent computer model can be used to monitor and optimize the actual industrial operations of copper smelting. It is applicable to simulation of almost all copper pyrometallurgical processes.

Simulation of rheological behavior of asphalt mixture with lattice model

A three-dimensional(3D) lattice model for predicting the rheological behavior of asphalt mixtures was presented.In this model asphalt mixtures were described as a two-phase composite material consisting of asphalt sand and coarse aggregates distributed randomly.Asphalt sand was regarded as a viscoelastic material and aggregates as an elastic material.The rheological response of asphalt mixture subjected to different constant stresses was simulated.The calibrated overall creep strain shows a good approximation to experimental results.

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.

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.

Metallurgical modeling of microcrack repairment during welding nonferrous materials: non-equilibrium solidification behavior of weld pool (Ⅰ)

Metallurgical modeling of synergistic microcrack self-repairmen during welding single crystal and polycrystalline superalloys of high-temperature aerospace materials has been properly established. The idea of improvement of nickel-based superalloys weldability through non-equilibrium solidification behavior of backfill to self-repair arterial crack network is usefully proposed. Crystallographic control strategy of crack self-repairmen of fusion zone interdendritic solidification cracking and heat-affected zone （HAZ） intergranular liquation cracking is technically achievable, indicating that optimal niobium alloying beneficially refines weld microstructure, stabilizes the primary solidification path, increases the solidification temperature and concomitantly decreases the weld pool geometry. High-carbon grain boundary is more thermal stable and less contributes to incipient intergranular liquid film than that of low-carbon grain boundary. The theoretical predictions of cracking susceptibility are indirectly verified in a rather satisfactory manner. Additionally, the metallurgical modeling enhances predicative capabilities and thereby is readily applicable for other alloy systems.

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.

Deformation behavior of SiC particle reinforced Al matrix composites based on EMA model

Effects of the matrix properties,particle size distribution and interfacial matrix failure on the elastoplastic deformationbehavior in Al matrix composites reinforced by SiC particles with an average size of 5μm and volume fraction of 12%werequantitatively calculated by using the expanded effective assumption(EMA)model.The particle size distribution naturally bringsabout the variation of matrix properties and the interfacial matrix failure due to the presence of SiC particles.The theoretical resultscoincide well with those of the experiment.The current research indicates that the load transfer between matrix and reinforcements,grain refinement in matrix,and enhanced dislocation density originated from the thermal mismatch between SiC particles and Almatrix increase the flow stress of the composites,but the interfacial matrix failure is opposite.It also proves that the load transfer,grain refinement and dislocation strengthening are the main strengthening mechanisms,and the interfacial matrix failure and ductilefracture of matrix are the dominating fracture modes in the composites.The mechanical properties of the composites strongly dependon the metal matrix.

Numerical Simulation of Motor Vehicles’ Courtesy Behavior on Crosswalk Based on Car-Following Model

In observing driver courtesy towards pedestrians at unsignalized crosswalks, a behavioral model was adopted in a simulation based on the GM Car-Following Model. The SIMI Motion Software was used to extract the vehicle operation data from Wenyi South Road and Hanyuan Road in Xi'an City. The parameters of the GM Car-Following Model were calibrated by genetic algorithm. The road simulation environment based on the Car-Following Model was constructed by MATLAB. In the case of no stopping, uniform deceleration avoidance with advance notice, emergency brake avoidance without advance notice, changes such as the displacement of the Car-Following queue, headway, speed, acceleration, and deceleration were analyzed by numerical simulation. The results show that when there is advance notice before the crosswalk, the minimum headway distances of Car1-Car2, Car2-Car3, Car3-Car4 and Car4-Car5 are 7.09 m, 7.38 m, 7.65 m, 7.91 m, and the average rates of change of the headway during deceleration are 0.78 m/s, 0.74 m/s, 0.71 m/s, 0.68 m/s respectively;in the absence of advance notice before the crosswalk, the minimum headway distances of Car1-Car2, Car2-Car3, Car3-Car4 and Car4-Car5 are 7.28 m, 7.75 m, 8.19 m, 8.59 m, and the average rates of change of the headway during deceleration are 1.57 m/s, 1.25 m/s, 1.04 m/s, 0.96 m/s, respectively. Therefore, in order to effectively prevent the occurrence of vehicle rear-end events, it's necessary to set traffic signs and markings on the preceding section of the intersection or road exhibiting behavioral comity.

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.