借助外力 让感觉升华为思维——基于“Working Model”对2023年新课标卷第6题的拓展分析

“Working Model”是一个物理仿真模拟平台,可直观展示动力学中的物理过程和运动图像,形成真实的感觉。该平台可用于辅助教学,帮助学生通过感觉、知觉、记忆、想象、思维等认知过程来理解和掌握物理概念和规律。以2023年新课标卷第6题为切入点,结合近三年全国高考真题为例,探讨借助外力将感觉升华为思维的可能性,通过对“Working Model”的拓展分析提出一种新的思维模式,旨在帮助学生通过直观刺激和辅助工具将感觉体验转化为深度思考和创新思维。并通过理论分析和实证研究,探讨这种思维模式的实施方法、可行性和效果,为教育教学和认知科学领域的研究提供新的思路和启示。

Working Model在高中物理教学中的应用——以力学模型为例

基于Working Model的仿真实验功能,结合几个常见的力学运动模型展示Working Model在中学物理教学中的用途.利用Working Model将运动过程直观呈现,同时以数值、矢量、动态图像等输出形式将位移、速度和加速度等物理量同步反馈,以此进一步探究物理规律.

A Study on the Work Process-Based Practical Training Model for Basic Nursing Skills in Vocational Colleges

Objective:To explore and analyze the work process-based practical training teaching model for basic nursing skills in vocational colleges and its implementation effects.Methods:A total of 82 nursing students from our school were selected for the study,which was conducted from April 2023 to April 2024.Using a random number table method,the students were divided into an observation group and a control group,each with 41 students.The control group received conventional practical training teaching,while the observation group followed the work process-based practical training model for basic nursing skills.The assessment scores and teaching satisfaction of the two groups were compared.Results:The comparison of assessment scores showed that the observation group performed significantly better than the control group(P<0.05).The comparison of teaching satisfaction also indicated that the observation group had significantly higher satisfaction than the control group(P<0.05).Conclusion:The work process-based practical training teaching model for basic nursing skills in vocational colleges can improve students’assessment scores and enhance teaching satisfaction,demonstrating its value for wider application.

基于Working Model 2D运动仿真的机构设计

介绍了基于Working Model 2D运动仿真的机构设计。该文利用该软件对四杆机构进行运动仿真和运动分析,结合Excel实现凸轮机构的凸轮轮廓线的设计并作运动仿真。此软件简单易学,仿真过程形象直观,为机构设计提供了一个极好的工具。

基于Working model自卸汽车举升机构的动力学分析与研究

本文运用working model软件,以自卸汽车举升机构为一工程事例,建立其动力学仿真模型,并对此机构进行动力学仿真分析,分析所得结果对机械设计提供了依据。本文所采用的分析方法,具有很强的实践应用性,对设计工作有一定的指导意义。

基于Working model吊车机构的动力学分析与研究

运用Working model软件以吊车机构为工程事例,建立其动力学仿真模型,并对此机构进行动力学仿真分析,所得结果对机械设计提供了依据。

Working model运动仿真在物理教学中的应用

简单介绍Working model软件的功能以及在物理教学中的应用,它既可以进行运动仿真,同时也可以对物体的运动进行分析。本文结合一些简单的实例做出说明。

Vapor-Liquid Equilibrium Prediction of Ammonia-Ionic Liquid Working Pairs of Absorption Cycle Using UNIFAC Model

On the basis of reported experimental vapor-liquid equilibrium （VLE） data of NH3-1-ethyl-3-methylimidazolium acetate （NH3-[Emim]Ac）, NH3-1-butyl-3-methylimidazolium tetrafluoroborate （NH3-[Bmim][BF4]）, NH3-1,3-dimethylimidazolium dimethyl phosphate （NH3-[Mmim]DMP） and NH3-1-ethyl-3-methylimidazolium ethylsulfate （NH3-[Emim]EtOSO3） binary systems, the interaction parameters of 14 new groups have been regressed by means of the UNIFAC model. To validate the reliability of the method, these parameters have been used to calculate the VLE data with the average relative deviation of pressures of less than 9.35%. The infinite dilution activity coefficient （ γ1∞ ） and the absorption potential （ φ1 ） are important evaluation criterions of the affinity between working pair species of the absorption cycle. The UNIFAC model is implemented to predict the values of and φ1 of t6 sets of NH3-ionic liquid （1L） systems. The work found that the φ1 gradually increases following the impact order： φ1（[Cnmim][BF4]）〈φ1（[Cnmim]EtOSO3）〈φ1（[Cnmim]DMP）〈φ1（[Cnmim]Ac） （n= 1, 2, 3, … ） at a given cation of IL species and constant temperature, and φ1（[Mmim]X）〈φ1（[Emim]X）〈φ1（[Pmim]X）〈 φ1（[Bmim]X）（X= Ac, [BF4], DMP or EtOSO3） at a given anion of IL species and constant temperature. Furthermore, the φ1 gradually increases with increasing temperature. Then, it could be concluded that the working pair NH3-[BmimlAc has the best potential research value relatively.

Effect of working parameters on performance characteristics of hydrostatic turntable by using FSI-thermal model

Effects of working parameters on performance characteristics of hydrostatic turntable are researched by applying the fluid-structure-thermal coupled model.Fluid-structure interaction(FSI)technique and computational fluid dynamics(CFD)method are both employed by this new model,and thermal effects are also considered.Hydrostatic turntable systems with a series of oil supply pressures,various oil recess depth and several surface roughness parameters are studied.Performance parameters,such as turntable displacement,system flow rate,temperature rise of lubrication,stiffness and damping coefficients,are derived from different working parameters(rotational speed of turntable and exerted external load)of the hydrostatic turntable.Numerical results obtained from this FSI-thermal model are presented and discussed,and theoretical predictions are in good agreement with the experimental data.Therefore,this developed model is a very useful tool for studying hydrostatic turntables.The calculation results show that in order to obtain better performance,a rational selection of the design parameters is essential.

An implementation of cellular automaton model for single-line train working diagram

According to the railway transportation system＇s characteristics, a new cellular automaton model for the single- line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train（s） pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

Modeling of microstructure evolution of AZ80 magnesium alloy during hot working process using a unified internal state variable method

In this paper, a unified internal state variable(ISV) model for predicting microstructure evolution during hot working process of AZ80 magnesium alloy was developed. A novel aspect of the proposed model is that the interactive effects of material hardening, recovery and dynamic recrystallization(DRX) on the characteristic deformation behavior were considered by incorporating the evolution laws of viscoplastic flow, dislocation activities, DRX nucleation and boundary migration in a coupled manner. The model parameters were calibrated based on the experimental data analysis and genetic algorithm(GA) based objective optimization. The predicted flow stress, DRX fraction and average grain size match well with experimental results. The proposed model was embedded in the finite element(FE) software DEFORM-3 D via user defined subroutine to simulate the hot compression and equal channel angular extrusion(ECAE) processes. The heterogeneous microstructure distributions at different deformation zones and the dislocation density evolution with competitive deformation mechanisms were captured.This study can provide a theoretical solution for the hot working problems of magnesium alloy.

Model Parameter Transfer for Gear Fault Diagnosis under Varying Working Conditions

Gear fault diagnosis technologies have received rapid development and been effectively implemented in many engineering applications.However,the various working conditions would degrade the diagnostic performance and make gear fault diagnosis(GFD)more and more challenging.In this paper,a novel model parameter transfer(NMPT)is proposed to boost the performance of GFD under varying working conditions.Based on the previous transfer strategy that controls empirical risk of source domain,this method further integrates the superiorities of multi-task learning with the idea of transfer learning(TL)to acquire transferable knowledge by minimizing the discrepancies of separating hyperplanes between one specific working condition(target domain)and another(source domain),and then transferring both commonality and specialty parameters over tasks to make use of source domain samples to assist target GFD task when sufficient labeled samples from target domain are unavailable.For NMPT implementation,insufficient target domain features and abundant source domain features with supervised information are fed into NMPT model to train a robust classifier for target GFD task.Related experiments prove that NMPT is expected to be a valuable technology to boost practical GFD performance under various working conditions.The proposed methods provides a transfer learning-based framework to handle the problem of insufficient training samples in target task caused by variable operation conditions.

Optimization of the Conceptual Model of Green-Ampt Using Artificial Neural Network Model (ANN) and WMS to Estimate Infiltration Rate of Soil (Case Study: Kakasharaf Watershed, Khorram Abad, Iran)

Determination of the infiltration rate in a watershed is not easy and in empirical and theoretical point of view, it is important to access average value of infiltration. Infiltration models has main role in managing water sources. Therefore different types of models with various degrees of complexity were developed to reach this aim. Most of the estimating methods of soil infiltration are expensive and time consuming and these methods estimate infiltration with hypothesis of zero slope. One of the conceptual and physical models for estimating soil infiltration is Green-Ampt model which is similar to Richard model. This model uses slope factor in estimating infiltration and this is the power point of Green-Ampt model. In this research the empirical model of Green-Ampt was optimized with integrating artificial neural network model (ANN) and a model of geographical information system WMS to estimate the infiltration in Kakasharaf watershed. Results of the comparison between the output of this method and real value of infiltration in region (through multiple cylinders) showed that this method can estimate the infiltration rate of Kakasharaf watershed with low error and acceptable accuracy (Nash-Sutcliff performance coefficient 0.821, square error 0.216, correlation coefficient 0.905 and model error 0.024).

Rapid Modeling of an Excavator Working Device Based on the Secondary Development of Pro/E

In order to shorten the design cycle of the excavator working device, we have proposed a rapid modeling method for the excavator working device which uses parameters. Based on the Pro/toolkit, which is secondary development tool of Pro/E4.0,and combined with Vs C＋＋2005 programming software. It developed a flexible set of MFC visualization-friendly interfaces. Users can enter data in the visual interface according to their needs and it will generate a new part model quickly. So it improves the design quality, shortens the design cycle, and makes the cost lower significantly.

Mechanical stress and deformation analyses of pressurized cylindrical shells based on a higher-order modeling

In this research,mechanical stress,static strain and deformation analyses of a cylindrical pressure vessel subjected to mechanical loads are presented.The kinematic relations are developed based on higherorder sinusoidal shear deformation theory.Thickness stretching formulation is accounted for more accurate analysis.The total transverse deflection is divided into bending,shear and thickness stretching parts in which the third term is responsible for change of deflection along the thickness direction.The axisymmetric formulations are derived through principle of virtual work.A parametric study is presented to investigate variation of stress and strain components along the thickness and longitudinal directions.To explore effect of thickness stretching model on the static results,a comparison between the present results with the available results of literature is presented.As an important output,effect of micro-scale parameter is studied on the static stress and strain distribution.

Accounting for Heterogeneity in Stop Frequency Models of Work Tours Using Latent Class Poisson Models

Stop frequency models, as one of the elements of activity based models, represent an important part of travel behavior. Unobserved heterogeneity across the travelers should be taken into consideration to prevent biasedness and inconsistency in the estimated parameters in the stop frequency models. Additionally, previous studies on the stop frequency have mostly been done in larger metropolitan areas and less attention has been paid to the areas with less population. This study addresses these gaps by using 2012 travel data from a medium sized U.S. urban area using the work tour for the case study. Stop in the work tour were classified into three groups of outbound leg, work based subtour, and inbound leg of the commutes. Latent Class Poisson Regression Models were used to analyze the data. The results indicate the presence of heterogeneity across the commuters. Using latent class models significantly improves the predictive power of the models compared to regular one class Poisson regression models. In contrast to one class Poisson models, gender becomes insignificant in predicting the number of tours when unobserved heterogeneity is accounted for. The commuters are associated with increased stops on their work based subtour when the employment density of service-related occupations increases in their work zone, but employment density of retail employment does not significantly contribute to the stop making likelihood of the commuters. Additionally, an increase in the number of work tours was associated with fewer stops on the inbound leg of the commute. The results of this study suggest the consideration of unobserved heterogeneity in the stop frequency models and help transportation agencies and policy makers make better inferences from such models.

基于供需理论的生成式人工智能赋能情报工作范式模型构建与应用研究

[目的/意义]当前生成式人工智能的发展对社会产生了强烈冲击。为响应国家创新发展的迫切需求,如何利用生成式人工智能更好地完成情报工作,以满足用户的情报需求,已成为当前情报学领域关注的热点问题。[方法/过程]基于供需理论提出从数据供给侧(Supply)、智慧情报分析中台(Analysis)、情报需求侧(Demand)三方构建生成式人工智能赋能情报工作范式模型——SAD范式模型,深入分析生成式人工智能赋能情报工作机理,并结合国际前沿项目案例探讨生成式人工智能与情报工作的前瞻性融合发展。[结果/结论]生成式人工智能赋能情报工作范式模型SAD,可以更好地促进生成式人工智能赋能情报工作的各个环节,提高情报工作效率,为情报工作范式研究提供了新思路。

远程办公背景下工作不可预测性对工作与家庭冲突的影响——一个有调节的中介模型

远程办公已成为数字化工作实践的常态,ICT技术使用过程中和工作与家庭生活相关的负面影响越来越受到信息系统领域学者们的重视。本研究运用工作家庭资源理论模型,探究员工在远程办公情境下适应数字技术以及体验工作形式和工作方式转变的过程中感知到的新型工作压力,并阐释其损害员工家庭领域繁荣的具体路径。问卷调查结果表明,远程办公情境下的工作不可预测性导致员工心理弹性的应对资源减少,造成了工作与家庭冲突,而自尊可以有效地帮助员工缓解工作压力和恢复个人资源。实证结果为远程办公如何影响员工的工作体验以及工作与家庭关系提供了新的见解和启示。

数字经济时代管理咨询行业情报工作胜任力模型优化研究

[目的/意义]随着新一轮科技革命和产业变革不断深入,管理咨询行业日益受到重视,尤其在当前数字经济背景下,根据管理咨询行业目前的发展情况,急需对情报工作胜任力模型优化升级,为我国对管理咨询行业情报工作的有效管理提供科学参考。[方法/过程]梳理目前管理咨询企业中情报工作者胜任力不明确而造成的人才流失严重、高学历与复合型人才稀缺、人才选择与培养机制不完善等问题,在研究中通过词频统计法确定胜任特征、问卷调查法验证胜任力模型,并采用灰色关联度法对胜任力模型进行优化得出最终的情报工作胜任力模型。[结果/结论]针对情报工作者胜任力不明确这一根本原因,以优化后的胜任力模型为基础,从个人、企业、政府三个方面对管理咨询行业情报胜任力提升给出科学建议。

Latent Growth Mixture Modeling to Estimate Differential PTSD Trajectories and Associated Risk Factors in Psychiatric Staff Following Workplace Violence

Background: Workplace violence (WV) towards psychiatric staff has commonly been associated with Posttraumatic Stress Disorder (PTSD). However, prospective studies have shown that not all psychiatric staff who experience workplace violence experience post-traumatic stress. Purpose: We want to examine the longitudinal trajectories of PTSD in this population to identify possible subgroups that might be more at risk. Furthermore, we need to investigate whether certain risk factors of PTSD might identify membership in the subgroups. Method: In a sample of psychiatric staff from 18 psychiatric wards in Denmark who had reported an incident of WV, we used Latent Growth Mixture Modelling (LGMM) and further logistic regression analysis to investigate this. Results: We found three separate PTSD trajectories: a recovering, a delayed-onset, and a moderate-stable trajectory. Higher social support and negative cognitive appraisals about oneself, the world and self-blame predicted membership in the delayed-onset trajectory, while higher social support and lower accept coping predicted membership in the delayed-onset trajectory. Conclusion: Although most psychiatric staff go through a natural recovery, it is important to be aware of and identify staff members who might be struggling long-term. More focus on the factors that might predict these groups should be an important task for psychiatric departments to prevent posttraumatic symptomatology from work.