The next industrial revolution: Integrated services and goods

The outputs or products of an economy can be divided into services products and goods products (due to manufacturing,construction,agriculture and mining).To date,the services and goods products have,for the most part,been separately mass produced.However,in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods,the next - or third - industrial revolution is focused on the integration of services and/or goods; it is beginning in this second decade of the 21st Century.The Third Industrial Revolution(TIR) is based on the confluence of three major technological enablers(i.e.,big data analytics,adaptive services and digital manufacturing);they underpin the integration or mass customization of services and/or goods.As detailed in an earlier paper,we regard mass customization as the simultaneous and real-time management of supply and demand chains,based on a taxonomy that can be defined in terms of its underpinning component and management foci.The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced - as "servgoods" - in real-time,resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers.     

GENERALIZED LANDSCAPE THEORY:AGENT-BASED APPROACH TO ALLIANCE FORMATIONS IN CIVIL AVIATION INDUSTRY

1 IntroductionThe purpose of this Paper is to generalize Landscape theory[1] proposed by R.AXeirod and,then, to apply it to the civil aviation industry for simulating ajliance formation in it.Landscape theory provides a well-known agent-based simulation model for analyzing andpredicting alliance (or coalition) formation process. The theory makes two basic assumptions.The first assumption is that an agent is myopic in its assessments. In Other words, an agenteclates how well it gets along wi…     

基于PtolemyⅡ的自主飞行器控制系统代码生成及应用

为解决自主飞行器控制系统设计中存在的复杂的代码制造问题,引入基于计算模型的设计方法,使用适合于控制系统建模的同步数据流计算模型来指导模型中各个模块之间的交互通讯,通过进行静态分析决定模块的执行顺序并能以此产生相应代码。在Ptolemy II图形语言开发环境下,以同步数据流计算模型对自主飞行器实时控制系统进行有效建模,并在此计算模型指导下自动生成代码,而所生成的代码能实施在实时分布式计算平台上,实现自主飞行器单机自主飞行的硬件在环仿真。     

科研院所衍生企业转化动机对企业绩效的影响：市场扰动的调节作用

中美贸易战以来，国内科技企业的市场环境受到了较大的扰动。通过对中科院衍生企业进行调查得到的一手数据进行分析，研究发现，不同类型的转化动机中资金、学习和使命对企业绩效具有不同的影响，市场扰动对衍生企业的学习动机对企业绩效的影响具有负向调节作用。研究结果表明，政府和科研院所应鼓励衍生企业的各类转化动机，对以学习为动机创办的衍生企业可以给予适当的政策倾斜，以保障此类企业应对外部环境的市场扰动。     

A calculus for services innovation

Innovation in the services area - especially in the electronic services （e-services） domain - can be systematically developed by first considering the strategic drivers and foci, then the tactical principles and enablers, and finally the operational decision attributes, all of which constitute a process or calculus of services innovation. More specifically, there are four customer drivers （i.e., collaboration, customization, integration and adaptation）, three business foci （i.e., creation-focused, solution-focused and competition-focused）, six business principles （i.e., reconstruct market boundaries, focus on the big picture not numbers, reach beyond existing demand, get strategic sequence right, overcome organizational hurdles and build execution into strategy）, eight technical enablers （i.e., software algorithms, automation, telecommunication, collaboration, standardization, customization, organization, and globalization）, and six attributes of decision informatics （i.e., decision-driven, information-based, real-time, continuously-adaptive, customer-centric and computationally-intensive）. It should be noted that the four customer drivers are all directed at empowering the individual - that is, at recognizing that the individual can, respectively, contribute in a collaborative situation, receive customized or personalized attention, access an integrated system or process, and obtain adaptive real-time or just-in-time input. The developed process or calculus serves to identify the potential white spaces or blue oceans for innovation. In addition to expanding on current innovations in services and related experiences, white spaces are identified for possible future innovations; they include those that can mitigate the unforeseen consequences or abuses of earlier innovations, safeguard our rights to privacy, protect us from the always-on, interconnected world, provide us with an authoritative search engine, and generate a GDP metric that can adequately measure the growing knowledge economy,     

A Novel Hybrid FA-Based LSSVR Learning Paradigm for Hydropower Consumption Forecasting

Due to the nonlinearity and nonstationary of hydropower market data, a novel hybrid learning paradigm is proposed to predict hydropower consumption, by incorporating firefly algorithm(FA) into least square support vector regression(LSSVR), i.e., FA-based LSSVR model. In the novel model, the powerful and effective artificial intelligence(AI) technique, i.e., LSSVR, is employed to forecast hydropower consumption. Furthermore, a promising AI optimization tool, i.e., FA, is especially introduced to address the crucial but difficult task of parameters determination in LSSVR(e.g.,hyper and kernel function parameters). With the Chinese hydropower consumption as sample data,the empirical study has statistically confirmed the superiority of the novel FA-based LSSVR model to other benchmark models(including existing popular traditional econometric models, AI models and similar hybrid LSSVRs with other popular parameter searching tools), in terms of level and directional accuracy. The empirical results also imply that the hybrid FA-based LSSVR learning paradigm with powerful forecasting tool and parameters optimization method can be employed as an effective forecasting tool for not only hydropower consumption but also other complex data.     

基于状态机学习算法的TLS实现库安全性分析

通过状态机学习算法,可以提取传输层安全(transport layer security,TLS)协议的实现库状态机模型来分析其安全性。当前在状态机学习中需要解决状态机学习时间随目标系统状态数增长而呈指数级增长的问题。提出一种改进的状态机学习算法,通过TLS协议特定套接字约简所需测试序列;结合检查点算法构造测试序列的前缀树,简化目标系统对测试序列测试步骤。测试结果表明,提出的改进算法能够大幅减少状态机学习过程生成的等价查询数量,加速状态机学习过程。同时通过学习到的状态机模型,分析其异常状态,找到一个OpenSSl的逻辑错误,证明学习到的模型是有效的。     

Big Data: Unleashing information

At present,it is projected that about 4 zettabytes(or 10**21 bytes)of digital data are being generated per year by everything from underground physics experiments to retail transactions to security cameras to global positioning systems.In the U.S.,major research programs are being funded to deal with big data in all five sectors(i.e.,services,manufacturing,construction,agriculture and mining)of the economy.Big Data is a term applied to data sets whose size is beyond the ability of available tools to undertake their acquisition,access,analytics and/or application in a reasonable amount of time.Whereas Tien(2003)forewarned about the data rich,information poor(DRIP)problems that have been pervasive since the advent of large-scale data collections or warehouses,the DRIP conundrum has been somewhat mitigated by the Big Data approach which has unleashed information in a manner that can support informed-yet,not necessarily defensible or valid-decisions or choices.Thus,by somewhat overcoming data quality issues with data quantity,data access restrictions with on-demand cloud computing,causative analysis with correlative data analytics,and model-driven with evidence-driven applications,appropriate actions can be undertaken with the obtained information.New acquisition,access,analytics and application technologies are being developed to further Big Data as it is being employed to help resolve the 14 grand challenges(identified by the National Academy of Engineering in 2008),underpin the 10 breakthrough technologies(compiled by the Massachusetts Institute of Technology in 2013)and support the Third Industrial Revolution of mass customization.     

Applying Frameworks for Cognitive Services in IIoT

The technology,which enables creating new types of products,processes and services(i.e.,things),which outcomes alter traditional competition and industry boundaries and create new lasting value.The digitalization process uses digital technologies to provide the possibilities of new revenue and value-producing,i.e.,it changes business models and offers new value propositions.This change is ongoing.The most important ten strategic technology trends in 2019 include Edge computing,Blockchain,event and data-driven strategies,Digital Twins,and the maintenance of transparency(i.e.,traceability),Intelligent Apps and Analytics(Gartner 2018).In this paper,we experiment with the capabilities of intelligent applications to match the industrial business needs.This paper aims to bring insights closer to business objectives.Digitalization’s technological advantages can be achieved through data-driven strategies and wherein cognitive services are integrated into IoT(Internet of Things)and big data.We experiment with the Industrial IoT(IIoT)business models and value propositions to match the intelligent insights of cognitive solutions to business objectives.The IIoTs support and demand transparency and thus also data-driven objective insights,and because cognitive solutions can enhance insights on a product,a process or service and therefore provide measurable business objectives.Functional indicators enable interconnected smart things to collaborate.     

Safety-Critical Optimal Control for Autonomous Systems

This paper presents an overview of the state of the art for safety-critical optimal control of autonomous systems. Optimal control methods are well studied, but become computationally infeasible for real-time applications when there are multiple hard safety constraints involved. To guarantee such safety constraints, it has been shown that optimizing quadratic costs while stabilizing affine control systems to desired(sets of) states subject to state and control constraints can be reduced to a sequence of Quadratic Programs(QPs) by using Control Barrier Functions(CBFs) and Control Lyapunov Functions(CLFs). The CBF method is computationally efficient, and can easily guarantee the satisfaction of nonlinear constraints for nonlinear systems, but its wide applicability still faces several challenges. First, safety is hard to guarantee for systems with high relative degree, and the above mentioned QPs can easily be infeasible if tight or time-varying control bounds are involved. The resulting solution is also sub-optimal due to its myopic solving approach. Finally, this method works conditioned on the system dynamics being accurately identified. The authors discuss recent solutions to these issues and then present a framework that combines Optimal Control with CBFs, hence termed OCBF, to obtain near-optimal solutions while guaranteeing safety constraints even in the presence of noisy dynamics. An application of the OCBF approach is included for autonomous vehicles in traffic networks.     

INTERNET OF CONNECTED SERVGOODS:CONSIDERATIONS,CONSEQUENCES AND CONCERNS

In an earlier paper(Tien 2012),the author augurs that,in contrast to the first and second industrial revolutions which respectively focused on the development and the mass production of goods,the next-or third-industrial revolution is focused on the integration of services and/or goods;it began in this second decade of the 21 st Century.The Third Industrial Revolution(TIR) is underpinned by the integration or mass customization of services and/or goods.The benefits of real-time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced as "ServGoods",resulting in an overwhelming economic advantage to the industrialized countries where the consuming customers are at the same time the co-producing producers.Adding sensors to these ServGoods and letting them connect or communicate among themselves or with other ServGoods can result in an Internet of Things(i.e.,connected ServGoods).A number of considerations,consequences and concerns relating to such an Internet of Connected ServGoods are discussed herein.     

Charging Station Planning for Plug-In Electric Vehicles

A novel model for the charging station planning problem of plug-in electric vehicles is proposed in this paper considering the users’ daily travel. With the objective of minimizing the total cost, including the charging stations’ cost (including installing cost and management cost) and the users’ cost (including station access cost and charging cost), the proposed model simultaneously handles the problems where to locate the charging stations and how many chargers to be established in each charging station. Considering that different users may have different perception of station access cost and charging cost, two cases (i.e., homogeneous users and heterogeneous users) are typically investigated. The impacts of different discount rates, operating period of the charging stations, number of electric vehicles and number of charging stations on the location of the charging station are also studied. The simulation results not only show that it is very important to locate the charging stations according to the traveling behavior of users, but also verify the validity of the proposed model.     

面向自主飞行器的嵌入式计算平台

基于模型的设计方法是目前嵌入式控制系统开发与设计的主流方法,而对嵌入式控制系统模型及其代码正确性的检验是亟待解决的问题。基于平台的设计理论,提出一种面向自主飞行器的嵌入式计算平台,该平台以基于模型的设计方法实现对复杂实时控制系统建模,并且在同一框架下完成模型到代码的自动生成以及对实时控制系统进行不同粒度的检验,即X在环仿真,包括模型在环仿真、软件在环仿真、硬件在环仿真。该平台的提出为嵌入式实时控制系统的开发与设计提供了建模及模型检验的一体化环境,提高嵌入式实时控制系统的开发效率。     

A non-linear model for estimating the cost of achieving emission reduction targets: The case of the U.S., China and India

With the world talking about climate change,the United States(U.S.),China and India have announced their carbon emission reduction targets.For these three countries to achieve their targets, significant questions arise,such as what will be the annual emission reduction efforts to achieve those targets,how much it would cost and what would be the economic effects.This paper puts the carbon intensity reduction targets of China and India together with the absolute emission reduction target of the U.S.into the same non-linear model to quantitatively study the optimal emission control strategies and associated total cost for achieving those targets by the year 2020,and estimate and compare the minimized total costs of the three countries to reach their targets.Our results show that the total cost for the U.S.to achieve its emission reduction target is greater than those of China and India in terms of absolute amount.However,in terms of proportion of total cost to GDP,China and India’s ratios are significantly greater than that of the U.S.,indicating that for the developing countries such as China and India,the achievement of emission reduction targets needs relatively greater effort.     

在轨空间智能制造:分布式调度建模与优化

在轨空间制造系统是在行星大气层外的需要地面工厂、在轨空间工厂、天地运载工具协同的以进行空间设施建造为目标的一类分布式制造系统.分布式调度建模和高效优化求解技术是实现在轨空间智能制造的关键技术之一.本文针对一类具有组件地面分布式制造及运输、地空分批次运输、组件在轨装配等典型特点的在轨空间智能制造系统,将其分解为分布式同质流水线调度,考虑运输时间的同速并行机调度,考虑工件释放时间、机器可用时间、机器处理能力的单机批调度以及考虑组件释放时间、优先约束的单机调度等问题,并基于模型协调思想建立以最小化组件生产到产品装配总时长为目标的分布式多阶段调度模型.进而,将用于求解连续优化问题的易理优化算法扩展到离散调度问题,提出求解该分布式调度问题的基于易理优化的模因算法.基于中规模、大规模算例的仿真结果和算法分析比较表明:相较于粒子群算法、教学算法、水波算法等智能优化算法,所提算法是一种求解分布式多阶段调度问题的可行、有效算法.值得一提的是,这是第一篇关于在轨空间智能制造系统调度优化的研究.     

ON SERVICES RESEARCH AND EDUCATION

1. Pertinent Background The importance of the services sector can not be overstated (Tien, 2006); it employs a large and growing proportion of workers in the industrialized nations. As reflected in Table 1, the services sector includes a number of large industries; indeed, services employment in the U.S. is at 82.1 percent, while the remaining four economic sectors (i.e., manufacturing, agriculture, construction, and mining), which together can be considered to be the “goods” sector, emplo…     

人民币汇率的稳定机制及其动态过程(Ⅱ)——实证分析

首先应用协整方法检验人民币汇率、外汇储备、进出口及国际外汇市场的汇率（日元对美元的双边汇率）变化的可积性和变量之间的协整关系,进而建立用来描述人民币汇率由短期波动向长期均衡非线性调整的动态过程的误差修正模型．实证分析结果表明,模型的所有估计系数具有我们建模时设定的符号;并且人民币汇率、外汇储备及美元／日元汇率之间存在唯一的长期稳定关系,即协整关系;短期预测模型不仅具有令人满意的拟合效果和预测能力,而且具有结构稳定性     

反导半实物雷达与数学仿真模型的实时集成

基于VxWorks和高层体系结构(HLA),采用射频注入式仿真方法,对反导防御系统对目标进行探测、跟踪、识别、拦截和数据通信的全过程进行实时仿真集成。实验中干扰机为实装设备,雷达为半实物设备,其它均采用数学仿真模型。按照实时性约束采用三层体系结构:非实时层、弱实时层和强实时层。给出了系统的设计框架,重点分析了各关键数学模型的工作原理。实验结果表明,采用该体系结构能够有效地将实物设备、半实物设备和数学仿真模型集成起来,具有低成本、高效率、实时性和可靠性的特点。     

实际环境中多无人车协同路径规划模型研究

地面无人车的集群作战运用是当前人工智能与作战指挥交叉领域的热点研究问题。针对实际环境中多无人车无法满足动态威胁条件下的协同路径规划问题,采用全局路径规划算法A-star与局部路径规划算法RL相结合的思路,从感知到行为决策全交互协同的角度开展多无人车协同路径规划模型研究,设计协同作战态势威胁算法、状态与动作空间、奖励函数、势力范围函数;设计协同作战编队构型策略生成及打击路径动态优化子模型,完成基于自主学习的多无人车协同路径规划控制模型构建与求解。结果表明：该路径规划模型可有效应对复杂城市环境下多无人车协同路径规划任务需求。     

一个有害物品填埋场选址的决策支持系统

有害物品对环境和人类的危害正在日益加深，对于象中国这样的发展中国家来说有害物品的产量大、危害严重而处理率低。将各人口中心（如城镇）产生的有害物品运送到指定地点（填埋场）集中处理和存放是一条既经济又在技术上可行的方法。本文描述了一个支持有害物品填埋场选址优化决策的决策支持系统。该系统是一集成化的优化系统，它通过以下三个步骤完成优化决策：生成模型、优化模型、打印结果报告。有害物品填埋场选址问题一般涉及以下因素：第一，效率或成本，即填埋场同相关有害物品产生地间的总运输成本；第二，风险，即由于填埋场中的有害物品及运送有害物品的车辆会给填理场及沿途附近环境带来潜在的危害，因而象城镇这样的人口密集地均不希望靠近填埋场及所经路线；第三，风险公平性，填埋场选址的风险可能强加在一部分人头上而使其它相关群体没有或只有很少风险。本文在一个ＤＳＳ上实现了考虑上述目标的模型及优化算法，决策者可按组合方式构造特定情形下的优化选址模型，利用权衡表技术帮助决策者在有冲突目标的方案选择时对各种目标的权衡及其结果有直观地感受。本文对于选址问题的求解是基于优化算法的，因而它可以有效地求解相当复杂的同类问题。