Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

From the perspective of experimental practice: High-throughput computational screening in photocatalysis

Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.

Optimization of Grouping Evacuation Strategy in High-rise Building Fires Based on Graph Theory and Computational Experiments

It is difficult to rescue people from outside, and emergency evacuation is still a main measure to decrease casualties in high-rise building fires. To improve evacuation efficiency, a valid and easily manipulated grouping evacuation strategy is proposed. Occupants escape in groups according to the shortest evacuation route is determined by graph theory. In order to evaluate and find the optimal grouping, computational experiments are performed to design and simulate the evacuation processes. A case study shown the application in detail and quantitative research conclusions is obtained. The thoughts and approaches of this study can be used to guide actual high-rise building evacuation processes in future.

High-throughput computational screening and design of nanoporous materials for methane storage and carbon dioxide capture

The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.

A CASE STUDY IN THE APPLICATION OF SUPERSATURATED DESIGNS TO COMPUTER EXPERIMENTS

Supersaturated design is essentially a fractional factorial design in which the number of potential effects is greater than the number of runs. In this article, the supersaturated design is applied to a computer experiment through an example of steady current circuit model problem. A uniform mixed-level supersaturated design and the centered quadratic regression model are used. This example shows that supersaturated design and quadratic regression modeling method are very effective for screening effects and building the predictor. They are not only useful in computer experiments but also in industrial and other scientific experiments.

Computer modeling of high-pressure leaching process of nickel laterite by design of experiments and neural networks

Due to the complex chemical composition of nickel ores, the requests for the decrease of production costs, and the increase of nickel extraction in the existing depletion of high-grade sulfide ores around the world, computer modeling of nickel ore leaching process be- came a need and a challenge. In this paper, the design of experiments （DOE） theory was used to determine the optimal experimental design plan matrix based on the D optimality criterion. In the high-pressure sulfuric acid leaching （HPSAL） process for nickel laterite in ＂Rudjinci＂ ore in Serbia, the temperature, the sulfuric acid to ore ratio, the stirring speed, and the leaching time as the predictor variables, and the degree of nickel extraction as the response have been considered. To model the process, the multiple linear regression （MLR） and response surface method （RSM）, together with the two-level and four-factor full factorial central composite design （CCD） plan, were used. The proposed re- gression models have not been proven adequate. Therefore, the artificial neural network （ANN） approach with the same experimental plan was used in order to reduce operational costs, give a better modeling accuracy, and provide a more successful process optimization. The model is based on the multi-layer neural networks with the back-propagation （BP） learning algorithm and the bipolar sigmoid activation function.

Design and Implementation of Virtual Experiments for Computer Architecture Based on Simulators

In china,many students are unable to do experiments in computer architecture courses,which is very important in helping them to understand many key points.The reason is that the cost of the hardware required is too much.Besides,it is very difficult to do research study in hardware experiments.In our course,we adopted an alternative way to deal with the problem: to use software simulators,and designed a set of virtual experiments based on these simulators,which are described in detail in this paper.

A framework for equipment systems-of-systems effectiveness evaluation using parallel experiments approach

Equipment systems-of-systems （SOS） effectiveness evaluation can provide important reference for construction and optimization of the equipment SoS. After discussing the basic theory and methods of parallel experiments, we depict an SoS effectiveness analysis and evaluation method using parallel expe- riments theory in detail. A case study is carried out which takes the missile defense system as an example. An artificial system of the missile defense system is constructed with the multi-agent modeling method. Then, single factor, multiple factors and defense position deployment computational experiments are carried out and evaluated with the statistical analysis method. Experiment re- sults show that the altitude of the secondary interception missile is not the key factor which affects SoS effectiveness and putting the defense position ahead will increase defense effectiveness. The case study demonstrates the feasibility of the proposed method.

Comparison of numerical simulations and experiments in conical gas–solid spouted bed

Flow behavior of gas and particles in conical spouted beds is experimentally studied and simulated using the twofluid gas-solid model with the kinetic theory of granular flow.The bed pressure drop and fountain height are measured in a conical spouted bed of 100 mm I.D.at different gas velocities.The simulation results are compared with measurements of bed pressure drop and fountain height.The comparison shows that the drag coefficient model used in cylindrical beds under-predicted bed pressure drop and fountain height in conical spouted beds due to the partial weight of particles supported by the inclined side walls.It is found that the numerical results using the drag coefficient model proposed based on the conical spouted bed in this study are in good agreement with experimental data.The present study provides a useful basis for further works on the CFD simulation of conical spouted bed.

A study of the relationship between nurses'experience,structural empowerment,and attitudes toward computer use

Objective:This study examined the relationship between structural empowerment and nurses’experience and attitudes toward computer use.Methods:This study was conducted using a cross-sectional quantitative design.A total of 184 registered nurses from four hospitals in Jordan participated in the current study.Data were collected using a demographics questionnaire,the Conditions for Work Effectiveness Questionnaire-II(CWEQ-II),and the Pretest for Attitudes toward Computers in Healthcare(PATCH).Results:The median of experience in years among nurses was 5.0,ranging from one to 26 years.The mean score for the attitudes toward computer use was 61.90±11.38.Almost half of the participants,45.11%,were in the category of“feel comfortable using user-friendly computers.”The participants’mean average of the total structural empowerment was 12.40±2.43,and the values for its four subscales were:opportunity 3.57±0.87,resources 2.83±0.85,information 3.06±0.79,and support 2.95±0.86.The frequencies analysis revealed that most participants had a moderate level of empowerment(n¼127,69.02%).The bivariate correlation between nurses’experience and attitudes toward computer use was significant(r¼0.17,P<0.05).The relationship between the total structural empowerment score and attitudes toward computer use was positive but weak(r¼0.20,P<0.01).Conclusion:The results indicated that more experienced nurses are more reluctant toward computer use.However,creating an empowering work environment can facilitate nurses’attitudes toward computer use.

Architectural Teaching and Design Computing： A Didactic Experience in a Brazilian Architecture Course

In the last years, architectural practice has been confronted with a paradigm shift towards the application of digital methods in design activities. In this regard, it is a pedagogic challenge to provide a suitable computational background for architectural students, to improve their ability to apply algorithmic-parametric logic, as well as fabrication and prototyping resources to design problem solving. This challenge is even stronger when considering less favored social and technological contexts, such as in Brazil, for example. In this scenario, this article presents and discusses the procedures and the results from a didactic experience carried out in a design computing-oriented discipline, inserted in the curriculum of a Brazilian architecture course. Hence, this paper shares some design computing teaching experiences and presents some results on computational methods and creative approaches, with a view to contribute to a better understanding about the relations between logical thinking, mathematics and architectural design processes.

Construction and Practice of Cloud-based Experiment and Innovation Project Supporting Platform for Computer Science Education

Higher and more requirements on experiments and innovation projects of computer science courses is brought forward to promote the "Double First Class". For these requirements, the cloud-based experiment and innovation project supporting platform is introduced in this paper. On the one hand, the platform could satisfy the diversified resource requirements of both teachers and students in course experiments and innovation projects. On the other hand, the feature of "construct once and access anywhere" could achieve higher resource utilization rate and lower costs than the traditional "lab-based" experiment mode. The supporting platform has been applied to practice and gains a lot of positive feedbacks.

Teaching mechanism empowered by virtual simulation: Edge computing–driven approach

With the rapid development of network and communication techniques,the teaching forms have become diversified.To enhance the education experience and improve the teaching environment,an increasing number of educational institutions have adopted virtual simulation technology.A typical teaching mechanism is to exploit Virtual Reality(VR)technology,which affords participants an immersive experience.Unquestionably,such a VRbased mode is highly approved.However,the performance of this technology requires further optimization.On one hand,for VR 360video,the current intraframe decision cannot adapt to rapid response demands.On the other hand,the generated data size is considerably large and fast computation may not be realized,depending on the local VR device.Therefore,this study proposes an improved teaching mechanism empowered by edge computing–driven VR,called VE4T,that involves two parts.First,an intraframe decision algorithm for VR 360videos is devised to realize the rapid responses.Second,an edge computing framework is proposed to offload some tasks to an edge server for computation,where a task scheduling strategy is developed to check whether a task needs to be offloaded.Finally,experiments are performed using a practical teaching scenario with some VR devices.The obtained results demonstrate that VE4T is more efficient than existing mechanisms.

Statistical physics of human beings in games:Controlled experiments

It is important to know whether the laws or phenomena in statistical physics for natural systems with non-adaptive agents still hold for social human systems with adaptive agents, because this implies whether it is possible to study or understand social human systems by using statistical physics originating from natural systems. For this purpose, we review the role of human adaptability in four kinds of specific human behaviors, namely, normal behavior, herd behavior, contrarian behavior, and hedge behavior. The approach is based on controlled experiments in the framework of market-directed resource-allocation games. The role of the controlled experiments could be at least two-fold： adopting the real human decision-making process so that the system under consideration could reflect the performance of genuine human beings; making it possible to obtain macroscopic physical properties of a human system by tuning a particular factor of the system, thus directly revealing cause and effect. As a result, both computer simulations and theoretical analyses help to show a few counterparts of some laws or phenomena in statistical physics for social human systems： two-phase phenomena or phase transitions, entropy-related phenomena, and a non-equilibrium steady state. This review highlights the role of human adaptability in these counterparts, and makes it possible to study or understand some particular social human systems by means of statistical physics coming from natural systems.

近代物理实验课程的思政教育探索

围绕“三位一体”的人才培养目标,提出基于近代物理实验课程的思政建设体系。以金刚石NV色心量子计算实验为例,在优化教学目标的基础上,从回顾科学历史、了解前沿动态、夯实基础知识和自主拓展研究四个维度融入思政教育,丰富实验内容。利用智慧教学工具,采用启发式讲授法结合演示、小组讨论、自主合作探究和任务驱动等方法展开教学,改革传统授课方式。采用具有“导、学、练、展、评”五个教学环节的SPOC混合式教学模式并配合在线网络教学平台,以及现代教育技术手段拓展思政教育的空间维度,提升思政元素的融入效果,实现立德树人的根本任务。

蒽与马来酸酐Diels-Alder反应的量化计算研究——介绍一个计算化学实验

蒽与马来酸酐的Diels-Alder反应是基础有机化学实验课程中普遍开展的一个经典实验。本文推荐蒽与马来酸酐Diels-Alder反应的计算化学实验,该实验采用Gaussian 16程序中的密度泛函方法对蒽和马来酸酐Diels-Alder反应的反应机理进行了研究。旨在通过本实验激发学生对有机化学和计算化学的兴趣,加深学生对化学学科的理解,提升学生在科研工作中学以致用的能力。

雾气下心电监护仪界面视觉搜索效率研究

目的研究护目镜产生雾气情况下心电监护仪界面的字符大小及颜色一致性对信息视觉搜索效率的影响。方法通过模拟护目镜在不同雾气程度下的场景,控制不同字符大小、颜色一致性,考察三者对医护人员视觉搜索效率的影响。实验中37位被试依次完成眼动实验,记录其行为数据和眼动数据,深入探讨三种变量因素的交互效应。结果使用心电监护仪时不同雾气程度、字符大小、颜色一致性三种因素的交互效应显著,其中行为数据的三种因素交互效应显著P<0.001,眼动数据的三种因素交互效应显著P<0.05。未产生雾气与低雾气场景下,大字符、颜色不一致视觉搜索效率最高;中雾气与高雾气场景下,中字符、颜色不一致的视觉搜索效率最高。结论三种因素在不同条件下,交互效应的视觉搜索效率不同,设计人员可根据护目镜产生的雾气程度,调整心电监护仪界面字符大小与颜色一致性,以提升医护人员的视觉搜索效率。

基于CarSim/Simulink的计算机控制系统综合实验设计

针对计算机控制系统课程中控制算法设计与仿真实现,设计了基于CarSim/Simulink的控制综合实验方案。以4轮独立驱动小车为对象,要求学生熟悉其基本工作原理,并在非线性动力学模型基础上,进行局部线性近似,设计反馈控制器,模拟小车控制。使用CarSim仿真软件可直观地模拟调整4轮独立驱动小车的质量、质心位置和转动惯量等,实现个性化选择,搭建车辆模型;与Simulink接口互通,在Simulink中完成控制算法。实验设计旨在使学生夯实计算机控制系统的理论基础,并逐步过渡到控制工程,理论联系实际,培养其解决复杂工程问题的能力。

PSCAD的发电机准同期并列综合实验设计

针对电力系统自动化实验教学中存在的不足,设计了同步发电机准同期并列综合实验。实验模型采用PSCAD/EMTDC,建立了包含发电机及并网系统、原动机及其调速器、励磁系统、准同期并列控制单元、电压向量的动态显示等关键部件。依托实验模型设计了循序渐进的教学实验项目,主要有机组启动与并网的验证性实验、不同并列条件影响的分析性实验、频率差和电压差调节的设计性实验。该实验将电路、电机学、自动控制理论、电力系统分析等多门专业核心课程贯穿起来,提升了学生综合运用知识解决复杂工程问题的能力。

量子机器学习综述

近年来,机器学习一直是被关注和探讨的研究热点,被应用到各领域并在其中起着重要作用.但随着数据量的不断增加,机器学习算法训练时间越来越长.与此同时,量子计算机表现出强大的运算能力.因此,有研究人员尝试用量子计算的方法解决机器学习训练时间长的问题,量子机器学习这一领域应运而生.量子主成分分析、量子支持向量机、量子深度学习等量子机器学习算法相继被提出,并有实验证明了量子机器学习算法有显著的加速效果,使得量子机器学习的研究展现出逐步走高的趋势.对量子机器学习算法进行综述.首先介绍量子计算基础;然后对量子监督学习、量子无监督学习、量子半监督学习、量子强化学习以及量子深度学习5类量子机器学习算法进行介绍;接着对量子机器学习的相关应用进行介绍并给出了算法实验;最后进行总结和展望.