The uncertainty recovery analysis for interdependent infrastructure systems using the dynamic inoperability input–output model

In this paper, an innovatory modelling framework is proposed to conduct the uncertainty recovery analysis for the interdependent infrastructure sectors based on the dynamic inoperability input–output model (DIIM). The DIIM captures the inoperability of infrastructure systems, and therefore can easily analyse how perturbations propagate among interconnected infrastructures and how to implement effective mitigation efforts after a disaster. In this paper, based on the random recovery time distribution, we apply the Monte Carlo simulation to obtain the distributions of the economic losses for the critical interdependent infrastructure sectors after a disaster. The proposed method can provide the decision-makers the guidance in making suitable risk-management decisions as well as how the risks can be mitigated, if the disaster cannot be avoided to happen in the first place.     

Supply-side inoperability input–output model (SIIM) for risk analysis in manufacturing systems

This paper proposes a methodological approach in risk analysis of interdependent manufacturing systems which is based on Ghosh model - a variation of the Leontief input-output model. The proposed approach is able to quantify the impact of supply perturbations in a manufacturing system in terms of cost-price increase in production output due to increase in prices of value-added input brought about by degraded supply resulting from natural or man-made disasters and sudden policy changes. Unlike demand-driven perturbation models presented in literature, the supply-driven inoperability input-output model (SIIM) appears to be more relevant particularly in make-to-order manufacturing systems as demand is usually pre-determined and production costs typically increase when prices of inputs increase. An actual case study was carried out in a furniture manufacturing firm in central Philippines and three scenarios were presented to illustrate the proposed approach: (1) a sudden log ban in the location of the supplier, (2) increase in labor costs and (3) metal shortage caused by severe weather condition. Results show that supply perturbation of upstream processes does not impact downstream processes as long as these processes remain independent of the perturbed upstream process as described in firm's system structure and topology. This also shows that the magnitude of impact of non-perturbed process depends on its nature of interdependence of the perturbed process. The proposed approach is highly relevant for manufacturing practitioners in formulating and implementing mitigation and adaptation policies.     

Linear optimal control of national econometric models

A control optimization approach is developed in this paper for the purpose of investigating the impact of alternative development strategies on the national economy of Egypt. Basic to this approach is the formulation of an aggregate econometric model and the manipulation of its performance as a linear quadratic tracking problem. The model comprises three major sectors ; namely agriculture, industry and services. Data processing and model parameter estimation and implementation are performed for the period 1961–1976 and further projected to the period 1976–1980. In light of the assumptions made, the obtained results are interpreted and found to be satisfactory.     

Developing a digital transformation process in the manufacturing sector: Egyptian case study

Digital transformation is of crucial importance in the manufacturing industry, especially after the COVID-19 pandemic because of the increasing need for remote working and socially distanced workplaces. However, there is a lack of a clear and well-defined process to implement digital transformation in manufacturing. This paper aims to identify the most critical stages to implementing digital transformation in the manufacturing sector. Twenty-one structured interviews with experienced specialists in digitalisation in the manufacturing sector in the Egyptian economy were held and used the Best–Worst Method to analyse the data as an analysis tool for a multiple criteria decision making (MCDM) approach. The digital transformation process comprises eight stages covering technology, management, communications, and customer elements. The main contribution of this work stage is the balance between the different elements of digital transformation—digital technologies, leadership and strategy, people and business processes—to create an integrated 8-step process of digital transformation in the manufacturing sector of developing economies such as the Egyptian economy.

     

服务业专业化集聚与服务业内部结构演进

服务业结构升级是当下中国经济面临的主要问题之一。本文试图从服务业专业化集聚的角度提供新的动力解释,研究发现服务业专业化集聚对服务业内部结构演进有正的显著的影响,它推动着服务业内部结构的升级和转型。本文先构建一个非均衡的增长模型分析服务业专业化集聚如何影响资源在各个部门间的流动,接着采用省际面板数据分析两者间的关系,最后,针对地区间指标显著的差异,采用分位数回归方法来进一步验证,结果表明,服务业专业化集聚对服务业内部结构演进有着正的影响的结论稳健可靠。     

Shape design sensitivity analysis of kinematical boundaries

A new approach is used in this paper to derive the design sensitivity formulation with kinematical design boundaries. By employing the concept of the conventional finite difference approach, the variation of structural response due to change of the kinematic design boundary can be represented by the perturbed structure under a set of kinematical boundary conditions. Parameterization of the design variation with respect to the design variable enables us to transform the design sensitivity into the solutions of a boundary value problem with perturbation displacements on the design boundary. The perturbation diplacements can be evaluated from the stress and displacement fields of the initial problem. This approach can be treated as a special case of the general direct formulation, but the derivation using the finite difference procedure gives a strong physical meaning of the method, and the formulation derived provides an explicit form for design sensitivity calculation. The numerical implementation of this approach based on the boundary element method is discussed, and a few numerical examples are used to verify the proposed formulation.     

Application of Vasileva's singular perturbation method to a problem in ecology

The simultaneous presence of fast and slow processes in ecological models leads to the formulation of model equations in a form amenable for the analysis by singular perturbation method. The method as originally proposed by Vasileva (1963) is applied to a specific species-resource logistic model and an algorithm useful for implementation on a digital computer is given. The solutions are obtained for zeroth, first and second order approximations. The accuracy of the solutions is examined by considering the integral-squared-error between the exact solutions and the perturbed solutions. The variation of this error with respect to the small parameter associated with the perturbation method is studied. An important result due to Tikhnov (1950) in the singular perturbation theory is illustrated. It is seen that Vasileva's singular perturbation method is a powerful analytical tool for investigations of various phenomena in the natural sciences.     

‘I-O-W’ model for national planning

The paper proposes an input-output-waste (I-O-W) model as an extension of the input-output model to incorporate waste management (WM) aspects in national planning. The waste aspects have not been explicitly considered in the existing literature on input-output economics. It is visualized that in the economic structure the waste parameter has a significant role to play, and the I-O-W model will be a closer representation of the economy than that of conventional input-output models. Any unnecessary input to or any undesirable output from the system is considered as waste. The basic framework of an I-O-W model is presented, which consists of a technology matrix, a final-demand matrix, and a WM policy matrix. The resource balance has been established by treating the input to be equal to the sum of output and waste. The technological coefficients are interlinked by wastivity indices. The projections of a hypothetical economy consisting of one production sector and one WM sector have been determined for material resources and for different WM policies.     

The role of R&D and corporate governance in Korea: IT firms versus non-IT firms

Recent economic development in Korea was mostly driven by companies in the IT sector. Also, it is widely argued that R&D investment has a positive impact on firm value, especially for IT firms. In this paper, we analyze how R&D investment has contributed to the growth of Korea’s economy by examining the effect of R&D investment on firms’ market value, measured as Tobin’s Q, and investigate whether this effect is different between firms in the IT sector and firms in the non-IT sector. We also account for the effect of another major change experienced by Korean firms: changes in corporate governance structure. We find that for firms in the IT industry, higher R&D investment coupled with high foreign ownership results in higher firm valuation.     

Central banking in a transitory economy: an adaptive control model for India

The purpose of this paper is to formulate a policy model for the Indian economy, incorporating an expectation generating mechanism in a formal way. The aim is to see how policies will change over time when the expectation of the private sector is changing. In a mixed economy planning has to take into account how the private sector formulates and revises its expectation regarding various government policies and their possible impacts on the endogenous variables (or target variables) in the economy. Normally in an economy like India's the government formulates its plan for the public sector over the next five years. The government can regulate the private sector by various means, such as licences, investment quotas, tax-subsidy rates, bank interest rates and by various monetary controls. The private sector, knowing the targets of the government, formulates its own expectations regarding the fulfulments of the targets (because it never expects that the government can fulfil its targets exactly) and possible movements of various policies. It behaves according to its expectations and realization of past expectations and thus allocates its resources. So the optimum design of public policies should be to direct the private sectors towards the desired goals defined by the planners, taking into account the reactions of the private sector. The purpose of public policy in such an environment should be to formulate different central bank policies regarding money stock, credit expansion and components of the money multiplier along with government discount rate, and the exchange rate so that the private sector would react in the desired way, given the goals set by the planners regarding national income, balance of payments, domestic absorptions and prices.     

A policy model for income growth and distribution using econometric and programming techniques: the Taiwan case

A computable general equilibrium model is developed by means of an extended input-output model under realistic constraints at two levels: sectoral and aggregative. Econometric estimates of sectoral production functions and a linear programming test that imposes resource and other constraints are performed for the economy of Taiwan to evaluate the trade-off between income growth and income equality, which is otherwise known as Kuznets hypothesis. Several policy scenarios, such as export promotion and import substitution as well as shortages of foreign exchange, are examined to evaluate their impact on the economy, its growth and the income distribution pattern.

The simulated profiles and linear programming experiments appear not to support the so-called Kuznets hypothesis for Taiwan in her drive towards industrial growth in recent years. This inference is upheld even when capital-labour substitution is econometrically estimated for each sector and then integrated with the input-output model     

Three-time scale multi-objective optimal PID control with filter design

This paper presents the design of a multi-objective PID (proportional, integral, and derivative) controller in three time scales for a system with load disturbances and sensor noise. The key to this design method is to divide the problem into three time scales by following a singular perturbation approach, which allows for the optimization of fewer parameters in each time scale instead of all the three PID gains at once, hence less computation and design effort. The optimization objectives are the minimization of the overshoot and peak time and the maximization of the closed-loop system's ability to reject noise and load disturbances. The impact of the integral action and filter on the optimal results is investigated by tuning the singular perturbation parameters. The obtained results show that the performance of the closed-loop system recovers the optimal solution, which is based on the fast subsystem, as the singular perturbation parameters get sufficiently small.     

Application of physical system theory and goal programming to modelling and analysis of waste management in national planning

Conventionally, national planning models have emphasized two major interfaces of the economic system, i.e. the input, and the output. The third important interface, i.e. waste, has not received the attention it deserves in the economic planning process. Attempts to include waste parameters in economic environmental modelling has been limited to tackling certain environmental considerations in national planning. The broader perspective of waste management (WM) has, by and large, been ignored in most of the literature in this context. This paper presents a graph theoretical system model of a multi-sectoral national economy including WM sectors. The system model of the economy has been integrated to a multi-objective goal programming model to fulfil the WM goals in a particular planning period. The model takes care of a variety of factors like resource structure, standard of living, sustained economic growth, waste recycling, environmental quality, etc. The model may be applied to determine the optimal quantity of waste to be generated in various sectors, and to assess optimal waste recycling efforts, along with the type of technology to be employed in various sectors. The application of the model has been illustrated by the example of a two sector economy having one production sector and one WM sector, and the sensitivity analysis has been carried out for alternate objective functions. Statistical analysis and the interpretation of the results are presented. The different variables and goals have been categorized as highly sensitive, moderately sensitive and less sensitive. The discussion of the results has been extended to show how the proposed model can be applied to real life national planning from a WM viewpoint.     

Unknown input observer design and analysis for networked control systems

The insertion of communication networks in the feedback loops of control systems is a defining feature of modern control systems. These systems are often subject to unknown inputs in a form of disturbances, perturbations, or attacks. The objective of this paper is to design and analyse an observer for networked dynamical systems with unknown inputs. The network effect can be viewed as either a perturbation or time-delay to the exchanged signals. In this paper, we (1) review an unknown input observer (UIO) design for a non-networked system, (2) derive the networked unknown input observer (N_etUIO) dynamics, (3) design a N_etUIO such that the effect of higher delay order terms are nullified and (4) establish stability-guaranteeing bounds on the networked-induced time-delay and perturbation. The formulation and results derived in this paper can be generalised to scenarios and applications where the signals are perturbed due to a different source of perturbation or delay.     

Homotopy perturbation method for solving sixth-order boundary value problems

In this paper, we apply the homotopy perturbation method for solving the sixth-order boundary value problems by reformulating them as an equivalent system of integral equations. This equivalent formulation is obtained by using a suitable transformation. The analytical results of the integral equations have been obtained in terms of convergent series with easily computable components. Several examples are given to illustrate the efficiency and implementation of the homotopy perturbation method. Comparisons are made to confirm the reliability of the homotopy perturbation method. We have also considered an example where the homotopy perturbation method is not reliable.     

具有左移左扇区稳定性的矩阵与多项式的最大非线性摄动边界

分别考虑矩阵与多项式的m方摄动族的鲁棒稳定性,稳定性区域为复平面上的左移左扇 区,给出了使上述族鲁棒稳定的参数最大摄动边界,并附有演示算例.     

一个基于离散事件仿真的Multi-Agent经济仿真模型

本文根据复杂系统及Multi-Agent仿真原理构建了一个简单的三部门经济仿真模型． 在模型中采用了学习算法模拟了经济个体的智能行为，并应用离散事件仿真技术实现了代理 人之间的交互与通信问题及系统的动态模拟，系统模拟了企业在亏损时退出与不退出市场这 两种策略下的经济运作状况，说明了亏损企业不退出市场不仅将引起更多企业的亏损，而且 会使宏观经济指标下降．     

A finite element formulation for beams with thin walled cross-sections

The paper presents a finite element model for calculation of stresses and deformations of beams with thin walled cross-sections. The beam model takes into account deformations due to shear. Warping is accounted for by a modified sector coordinate formulation. As interpolation functions between the seven degrees of freedom at each node are used the analytical solutions for the special case of a double symmetric cross-section. Therefore, depending on the external loading, each prismatic beam can in most cases be treated as a single element. The assembly of the beam elements to the global model is performed by use of transition matrices which assures compatibility between the elements in the sence of least squares.     

Perturbation LDA: Learning the difference between the class empirical mean and its expectation

Fisher's linear discriminant analysis (LDA) is popular for dimension reduction and extraction of discriminant features in many pattern recognition applications, especially biometric learning. In deriving the Fisher's LDA formulation, there is an assumption that the class empirical mean is equal to its expectation. However, this assumption may not be valid in practice. In this paper, from the “perturbation” perspective, we develop a new algorithm, called perturbation LDA (P-LDA), in which perturbation random vectors are introduced to learn the effect of the difference between the class empirical mean and its expectation in Fisher criterion. This perturbation learning in Fisher criterion would yield new forms of within-class and between-class covariance matrices integrated with some perturbation factors. Moreover, a method is proposed for estimation of the covariance matrices of perturbation random vectors for practical implementation. The proposed P-LDA is evaluated on both synthetic data sets and real face image data sets. Experimental results show that P-LDA outperforms the popular Fisher's LDA-based algorithms in the undersampled case.