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”.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for patients.Consequently,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient activities.These methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful consideration.Hence,this paper proposes a crossover-based Multilayer Perceptron(CMLP)model.The collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of patients.Once an attack is detected,healthcare professionals are promptly alerted to prevent data leakage.The paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are collected.Experimental results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient activities.Comparing the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and F1-score.Specifically,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

Carrying Capacity and Coupling Coordination of Water and Land Resources Systems in Arid and Semi-arid Areas: A Case Study of Yulin City, China

Quantitatively assessing the carrying capacity of water and land resources systems in arid and semi-arid areas is crucial for achieving the 2030 Sustainable Development Goals.In this work,taking Yulin City in China as a case study and employing the Criteria Importance Through Intercriteria Correlation(CRITIC)method,a modified model of coupling degree was developed to evaluate the car-rying capacity of water and land resources systems endowment and utilization,as well as their coupling coordination degree from 2013 to 2020.Our findings indicate that the water and land resources of Yulin are diminishing due to declines in agriculture,higher industrial water use,and wetland shrinkage.However,reallocating domestic water for ecological sustainability and reducing sloping farmland can mitigate this trend of decline.Temporally,as the coupling coordination between water and land resources system endowment in Yulin continuously improved,the coupling coordination between water and land resources system utilization first decreased and then in-creased with 2016 as the turning point.Spatially,the carrying capacity of water and land resources systems,the coupling coordination degree between water and land resources system endowment,and the coupling coordination degree between water and land resources system utilization in Yulin exhibited the same pattern of being higher in the six northern counties than in the six southern counties.Improving the water resources endowment is vital for the highly efficient use of water and land resources.

Personalized Health Monitoring Systems: Integrating Wearable and AI

The integration of wearable technologies and artificial intelligence (AI) has revolutionized healthcare, enabling advanced personal health monitoring systems. This article explores the transformative impact of wearable technologies and AI on healthcare, highlighting the development and theoretical application of the Integrated Personal Health Monitoring System (IPHMS). By integrating data from various wearable devices, such as smartphones, Apple Watches, and Oura Rings, the IPHMS framework aims to revolutionize personal health monitoring through real-time alerts, comprehensive tracking, and personalized insights. Despite its potential, the practical implementation faces challenges, including data privacy, system interoperability, and scalability. The evolution of healthcare technology from traditional methods to AI-enhanced wearables underscores a significant advancement towards personalized care, necessitating further research and innovation to address existing limitations and fully realize the benefits of such integrated health monitoring systems.

Comparison of German and American Higher Education Accreditation Systems and Implications for Quality Management of Higher Education in China

At the present stage,China’s higher education has experienced continuous reform and enhancement,the scale of education has jumped to the forefront,and the quality of education has been continuously improved,which has made gratifying achievements.The development of China’s higher education has entered the critical node of improving quality and efficiency,and the importance of quality management as the central link in improving the quality of higher education is self-evident.Accreditation as an effective means of quality assurance,in Germany and the United States has formed a mature and perfect system and procedures.Therefore,analysing and learning from the quality management system of higher education in Germany and the United States has an important reference value for promoting the further development of quality management of higher education in China.

Adoption of Solar Pumping Systems by Vegetable Farmers in Niayes Agro-Ecological Zone of Senegal: Adoption as a Sequential Process

This article examines the determinants of the adoption of solar pumping systems (PV) by vegetable farmers in the Niayes area of Senegal. To measure the determinants, we used a sequential logit model to translate the adoption process from becoming aware of solar pumping systems to testing them, i.e. using them at least once, and then continuing to use them over time. The results show that the main variables affecting awareness of the use of solar pumping systems (PV) are age, marital status, experience, access to credit, the farmer’s knowledge of climate change, the farmer’s origin in the Thiès region and length of time in the Niayes area. The first use of PVs is influenced by factors such as the size of the plot, the distance of the plot from the main road or from the market. Finally, the decision to adopt or continue use is influenced by gender, experience, household size and access to credit. Surprisingly, access to credit does not affect the first use of solar pumping systems, but plays a key role in their continued use.

Potential Driving Systems Associated with Extreme Rainfall across East Africa during October to December (OND) Season 2019

The East African (EA) region highly experiences intra-seasonal and inter-annual variation in rainfall amounts. This study investigates the driving factors for anomalous rainfall events observed during the season of October-November-December (OND) 2019 over the region. The study utilized daily rainfall data from Climate Hazards Group InfraRed Precipitation with Station Data Version 2 (CHIRPSv2) and the driving systems data. Statistical spatiotemporal analysis, correlation, and composite techniques were performed to investigate the teleconnection between OND 2019 seasonal rainfall and global synoptic climate systems. The findings showed that the OND 2019 experienced seasonal rainfall that was twice or greater than its seasonal climatology and varied with location. Further, the OND 2019 rainfall showed a positive correlation with the Indian Ocean Dipole (IOD) (0.81), Nino 3 (0.51), Nino 3.4 (0.47), Nino 4 (0.40), Pacific Decadal Oscillation (PDO) (0.22), and North Tropical Atlantic (NTA) (0.02), while El Nino-Southern Oscillation (ENSO) showed a negative correlation (−0.30). The region was dominated by southeasterly warming and humid winds that originated from the Indian Ocean, while the geopotential height, vertical velocity, and vorticity anomalies were closely related to the anomalous rainfall characteristics. The study deduced that the IOD was the major synoptic system that influenced maximum rainfall during the peak season of OND 2019. This study therefore provided insights on the diagnosis study of OND 2019 anomalous rainfall and its attribution over the EA. The findings of the study will contribute to improvements in forecasting seasonal rainfall by regional climate centers and national meteorological centers within the region.

Multiple Solutions for a Class of Singular Boundary Value Problems of Hadamard Fractional Differential Systems with p-Laplacian Operator

This paper discusses the existence and multiplicity of positive solutions for a class of singular boundary value problems of Hadamard fractional differential systems involving the p-Laplacian operator. First, for the sake of overcoming the singularity, sequences of approximate solutions to the boundary value problem are obtained by applying the fixed point index theory on the cone. Next, it is demonstrated that these sequences of approximate solutions are uniformly bounded and equicontinuous. The main results are then established through the Ascoli-Arzelà theorem. Ultimately, an instance is worked out to test and verify the validity of the main results.

基于SoS核函数调制的超声图像伪影剔除方法

针对超声图像伪影严重的问题,提出了一种基于SoS核函数调制的超声图像伪影剔除方法,该方法能同时剔除由等声程线扩散、传感器拖尾现象和检测噪声产生的伪影.该方法利用SoS核函数对测得的超声回波信号进行调制,对调制后的信号等间隔低速率采样来获取离散序列值,再对离散序列进行离散傅里叶变换得到傅里叶系数序列,利用谱估计算法对回波信号参数进行估计,获取检测信号的特征参数,最后对回波信号进行自适应重构,计算声场得到超声图像.试验结果表明,聚焦和直探头对槽和通孔类缺陷的去伪影效果明显,与传统B扫图像相比,峰值信噪比分别达到了24.306、23.213、15.074和16.444 dB,结构相似度分别为0.931、0.932、0.746和0.773,表明该算法有效提高了缺陷图像的质量.

基于SOS-LSTM的核电站隐蔽攻击方法研究

针对实现隐蔽攻击需要获取攻击目标高精度估计模型的问题,提出一种基于共生生物搜索算法优化长短期记忆神经网络(SOS-LSTM)的隐蔽攻击方法。首先,将攻击目标的反馈控制器输出和输入信号作为长短期记忆神经网络的数据集,通过训练得到受攻击区域的估计模型,再利用估计模型设计隐蔽攻击器向受攻击对象施加攻击信号。此外,使用SOS算法优化LSTM的网络参数来提升隐蔽攻击器的性能。对核电站一回路控制系统进行隐蔽攻击的仿真实验结果表明,该攻击方法在对目标控制系统输出信号实现预先设定攻击行为的同时具有较高隐蔽性。

一类不确定凸多项式优化的SOS松弛对偶问题

考虑一类目标函数和约束函数均具有谱面不确定数据的平方和(SOS)凸多项式优化问题.首先,借助SOS条件建立带有不确定数据的SOS凸多项式系统的择一性定理;其次,引入该SOS多项式优化问题的SOS松弛对偶问题,并刻画它们之间的鲁棒弱对偶性与强对偶性质;最后,借助数值算例说明该SOS松弛对偶问题可以重构为半定规划问题.

Conventional Geothermal Systems and Unconventional Geothermal Developments: An Overview

This paper provides an overview of conventional geothermal systems and unconventional geothermal developments as a common reference is needed for discussions between energy professionals. Conventional geothermal systems have the heat, permeability and fluid, requiring only drilling down to °C, normal heat flow or decaying radiogenic granite as heat sources, and used in district heating. Medium-temperature (MT) 100°C - 190°C, and high-temperature (HT) 190°C - 374°C resources are mostly at plate boundaries, with volcanic intrusive heat source, used mostly for electricity generation. Single well capacities are °C - 500°C) and a range of depths (1 m to 20 Km), but lack permeability or fluid, thus requiring stimulations for heat extraction by conduction. HVAC is 1 - 2 m deep and shallow geothermal down to 500 m in wells, both capturing °C, with °C are either advanced by geothermal developers at <7 Km depth (Enhanced Geothermal Systems (EGS), drilling below brittle-ductile transition zones and under geothermal fields), or by the Oil & Gas industry (Advanced Geothermal Systems, heat recovery from hydrocarbon wells or reservoirs, Superhot Rock Geothermal, and millimeter-wave drilling down to 20 Km). Their primary aim is electricity generation, relying on closed-loops, but EGS uses fractures for heat exchange with earthquake risks during fracking. Unconventional approaches could be everywhere, with shallow geothermal already functional. The deeper and hotter unconventional alternatives are still experimental, overcoming costs and technological challenges to become fully commercial. Meanwhile, the conventional geothermal resources remain the most proven opportunities for investments and development.

Prescribed Performance Tracking Control of Time-Delay Nonlinear Systems With Output Constraints

The problem of prescribed performance tracking control for unknown time-delay nonlinear systems subject to output constraints is dealt with in this paper. In contrast with related works, only the most fundamental requirements, i.e., boundedness and the local Lipschitz condition, are assumed for the allowable time delays. Moreover, we focus on the case where the reference is unknown beforehand, which renders the standard prescribed performance control designs under output constraints infeasible. To conquer these challenges, a novel robust prescribed performance control approach is put forward in this paper.Herein, a reverse tuning function is skillfully constructed and automatically generates a performance envelop for the tracking error. In addition, a unified performance analysis framework based on proof by contradiction and the barrier function is established to reveal the inherent robustness of the control system against the time delays. It turns out that the system output tracks the reference with a preassigned settling time and good accuracy,without constraint violations. A comparative simulation on a two-stage chemical reactor is carried out to illustrate the above theoretical findings.

Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications.Although there is an extensive literature on qualitative properties such as safety and liveness,there is still a lack of quantitative and uncertain property verifications for these systems.In uncertain environments,agents must make judicious decisions based on subjective epistemic.To verify epistemic and measurable properties in multi-agent systems,this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge(FCTLK).We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy epistemic interpreted systems.In addition,we provide a transformation algorithm from fuzzy epistemic interpreted systems to fuzzy Kripke structures,as well as transformation rules from FCTLK formulas to Fuzzy Computation Tree Logic(FCTL)formulas.Accordingly,we transform the FCTLK model checking problem into the FCTL model checking.This enables the verification of FCTLK formulas by using the fuzzy model checking algorithm of FCTL without additional computational overheads.Finally,we present correctness proofs and complexity analyses of the proposed algorithms.Additionally,we further illustrate the practical application of our approach through an example of a train control system.

Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

Anomalous time-reversal symmetric non-Hermitian systems

The conditions for the emergence of the non-Hermitian skin effect, as a unique physical response of non-Hermitian systems, have now become one of the hot research topics. In this paper, we study the novel physical responses of nonHermitian systems with anomalous time-reversal symmetry, in both one dimension and two dimensions. Specifically, we focus on whether the systems will exhibit a non-Hermitian skin effect. We employ the theory of generalized Brillouin zone and also numerical methods to show that the anomalous time-reversal symmetry can prevent the skin effect in onedimensional non-Hermitian systems, but is unable to exert the same effectiveness in two-dimensional cases.

Numerical simulation for the initial state of avalanche in polydisperse particle systems

Numerical simulation is employed to investigate the initial state of avalanche in polydisperse particle systems.Nucleation and propagation processes are illustrated for pentadisperse and triadisperse particle systems,respectively.In these processes,particles involved in the avalanche grow slowly in the early stage and explosively in the later stage,which is clearly different from the continuous and steady growth trend in the monodisperse system.By examining the avalanche propagation,the number growth of particles involved in the avalanche and the slope of the number growth,the initial state can be divided into three stages:T1(nucleation stage),T2(propagation stage),T3(overall avalanche stage).We focus on the characteristics of the avalanche in the T2 stage,and find that propagation distances increase almost linearly in both axial and radial directions in polydisperse systems.We also consider the distribution characteristics of the average coordination number and average velocity for the moving particles.The results support that the polydisperse particle systems are more stable in the T2 stage.

Quantum discord and its dynamics for multipartite systems

Quantum discord, one of the famous quantum correlations, has been recently generalized to multipartite systems by Radhakrishnan et al. Here we give analytical solutions of the quantum discord for a family of N-qubit quantum states. For the bipartite system, we derive a zero quantum discord which will remain unchanged under the phase damping channel. For multiparitite systems, it is found that the quantum discord can be classified into three categories and the quantum discord for odd-partite systems can exhibit freezing under the phase damping channel, while the freezing does not exist in the even-partite systems.

Bipartite consensus problems of Lurie multi-agent systems over signed graphs: A contraction approach

This paper examines the bipartite consensus problems for the nonlinear multi-agent systems in Lurie dynamics form with cooperative and competitive communication between different agents. Based on the contraction theory, some new conditions for the nonlinear Lurie multi-agent systems reaching bipartite leaderless consensus and bipartite tracking consensus are presented. Compared with the traditional methods, this approach degrades the dimensions of the conditions, eliminates some restrictions of the system matrix, and extends the range of the nonlinear function. Finally, two numerical examples are provided to illustrate the efficiency of our results.