Dynamic evaluation of digital and green development policies based on text mining of the PMC framework

Aiming to identify policy topics and their evolutionary logic that enhance the digital and green development(dual development)of traditional manufacturing enterprises,address weaknesses in current policies,and provide resources for refining dual development policies,a total of 15954 dual development-related policies issued by national and various departmental authorities in China from January 2000 to August 2023 were analyzed.Based on topic modeling techniques and the policy modeling consistency(PMC)framework,the evolution of policy topics was visualized,and a dynamic assessment of the policies was conducted.The results show that the digital and green development policy framework is progressively refined,and the governance philosophy shifts from a“regulatory government”paradigm to a“service-oriented government”.The support pattern evolves from“dispersed matching”to“integrated symbiosis”.However,there are still significant deficiencies in departmental cooperation,balanced measures,coordinated links,and multi-stakeholder participation.Future policy improvements should,therefore,focus on guiding multi-stakeholder participation,enhancing public demand orientation,and addressing the entire value chain.These steps aim to create an open and shared digital industry ecosystem to promote the coordinated dual development of traditional manufacturing enterprises.

面向现代造船企业的资源管理信息框架技术研究

对企业级信息平台建模技术进行了回顾,基于现代造船企业设计制作流程,对造船全过程的资源需求进行分析,提出了面向生产设计和生产计划的资源信息集成模型,构建了现代造船企业的资源管理信息框架,为船舶企业有效利用资源提供了参考模型。

Iterative optimal control based on support vector machine modeling within the Bayesian evidence framework

In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is powerful for the problems characterized by small samples, nonlinearity, high dimension and local minima, support vector regression models are developed for the optimal control of batch processes where end-point properties are required. The model parameters are selected within the Bayesian evidence framework. Based on the model, an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy. Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.

Agent-Based Simulation for Interconnection-Scale Renewable Integration and Demand Response Studies

This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.

A Virtual Work Approach to Modeling the Nonlinear Behavior of Steel Frames

The stiffness reduction is studied in detail of compact W-Shapes （wide-flange steel shapes） that results from yielding of the cross-section due to uniaxial bending and axial compression. Three-dimensional m-p-τ surface plots developed from detailed fiber element models of a W8x31 are used to develop a generalized material model for direct implementation in the virtual work method. A portal steel frame is used to illustrate the virtual work method with the nonlinear material model in a first-order, inelastic analysis implementation and in a second-order, inelastic analysis condition. The nonlinear modeling capabilities of MASTAN2 are used to verify the accuracy of the virtual work results and are found to be in very close agreement.

RANDOM SETS: A UNIFIED FRAMEWORK FOR MULTISOURCE INFORMATION FUSION

The more diverse the ways and means of information acquisition are,the more complex and various the types of information are. The qualities of available information are usually uncertain,vague,imprecise,incomplete,and so on. However,the information is modeled and fused traditionally in particular,name some of the known theories: evidential,fuzzy sets,possibilistic,rough sets or conditional events,etc. For several years,researchers have explored the unification of theories enabling the fusion of multisource information and have finally considered random set theory as a powerful mathematical tool. This paper attempts to overall review the close relationships between random set theory and other theories,and introduce recent research results which present how different types of information can be dealt with in this unified framework. Finally,some possible future directions are discussed.

On modeling of electrical cyber-physical systems considering cyber security

This paper establishes a new framework for modeling electrical cyber-physical systems(ECPSs),integrating both power grids and communication networks. To model the communication network associated with a power transmission grid, we use a mesh network that considers the features of power transmission grids such as high-voltage levels, long-transmission distances, and equal importance of each node. Moreover, bidirectional links including data uploading channels and command downloading channels are assumed to connect every node in the communication network and a corresponding physical node in the transmission grid. Based on this model,the fragility of an ECPS is analyzed under various cyber attacks including denial-of-service(Do S) attacks, replay attacks, and false data injection attacks. Control strategies such as load shedding and relay protection are also verified using this model against these attacks.

Comparative analyses of current three-dimensional numerical solar wind models

We present a comparative study of the most advanced three-dimensional time-dependent numerical simulation models of solar wind. These models can be classified into two categories： （I） theoretical, empirical and numerically based models and （Ⅱ） self-consistent multi-dimensional numerical magnetohydrodynamic （MHD） models. The models of Category I are used to sep- arately describe the solar wind solution in two plasma flows regions： transonic/trans-Alfvrnic and supersonic/super-Alfvenic, respectively. Models of Category II construct a complete, single, numerical solar wind solution through subsonic/sub-Alfvrnic region into supersonic/super-Alfvrnic region. The Wang-Sheeley-Arge （WSA）/ENLIL in CISM is the most successful space weather model that belongs to Category I, and the Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme （BATS-R-US） code in SWMF （Space Weather Modeling Framework） and the solar-interplanetary conservative element solution element MHD （SIP-CESE MHD） model in SWIM （Space Weather Integrated Model） are the most commonly-used models that belong to Category II. We review the structures of their frameworks, the main results for solar wind background studies that are essential for solar transient event studies, and discuss the common features and differences between these two categories of solar wind models. Finally, we conclude that the transition of these two categories of models to operational use depends on the availability of computational resources at reasonable cost and point out that the models＇ prediction capabilities may be improved by employing finer computational grids, incorporating more observational data and by adding more physical constraints to the models.

A framework for an integrated unified modeling language

The unified modeling language(UML) is one of the most commonly used modeling languages in the software industry.It simplifies the complex process of design by providing a set of graphical notations,which helps express the objectoriented analysis and design of software projects.Although UML is applicable to different types of systems,domains,methods,and processes,it cannot express certain problem domain needs.Therefore,many extensions to UML have been proposed.In this paper,we propose a framework for integrating the UML extensions and then use the framework to propose an integrated unified modeling language-graphical(iUML-g) form.iUML-g integrates the existing UML extensions into one integrated form.This includes an integrated diagram for UML class,sequence,and use case diagrams.The proposed approach is evaluated using a case study.The proposed iUML-g is capable of modeling systems that use different domains.

MODELING AND FORECASTING OF STOCK MARKETS UNDER A SYSTEM ADAPTATION FRAMEWORK

This paper adopts the concept of dynamic feedback systems to model the behavior of financial markets, or more specifically, the stock market from a dynamic system point of view. Based on a feedback adaptation scheme, the authors model the movement of a stock market index within a framework that is composed of an internal dynamic model and an adaptive filter. The output-error model is adopted as the internal model whereas the adaptive filter is a time-varying state space model with instrumental variables. Its input-output behavior, and internal as well as external forces are then identified. Special attention has also been paid to the recent financial crisis by examining the movement of Dow Jones Industrial Average （DJIA） as an example to illustrate the advantage of the proposed framework. Supported by time-varying causality tests, five influential factors from economic and sentiment aspects are introduced as the input of this framework. Testing results show that the proposed framework has a much better prediction performance than the existing methods, especially in complicated economic situations. An application of this framework is also presented with focuses on forecasting the turning periods of the market trend. Realizing that a market trend is about to change when the external force begins to exhibit clear patterns in its frequency responses, the authors develop a set of rules to recognize this kind of clear patterns. These rules work well for stock indexes from US, China and Singapore.

Component-based Model Integration Approach for Computer Numerical Control System Development

A component-based model integration framework for computer numerical control system design and development is presented.The model integrates modeling,simulation,verification and implementation in a uniform environment.The computer numerical control(CNC) modeling language with well defined syntax and unambiguous semantics is developed.Using the proposed CNC model integration method,a three axis milling system model is developed in the case study.The approach is an attempt to create an infrastructure to support the CNC system design in an efficient way,while at the same time guarantees the function and performance requirements with advanced capability of the system such as modularity,flexibility,reusability,etc.

A multi-scale cholera model linking between-host and within-host dynamics

We propose a multi-scale modeling framework to investigate the transmission dynamics of cholera. At the population level, we employ a SIR model for the between-host transmission of the disease. At the individual host level, we describe the evolution of the pathogen within the human body. The between-host and within-host dynamics are connected through an environmental equation that characterizes the growth of the pathogen and its interaction with the hosts outside the human body. We put a special emphasis on the within-host dynamics by making a distinction for each individual host. We conduct both mathematical analysis and numerical simulation for our model in order to explore various scenarios associated with cholera transmission and to better understand the complex, multi-scale disease dynamics.