The spatial components of demographic change

"In recent years, fertility in developed countries has drastically fallen towards replacement levels, so that further changes play an increasing role in determining the dynamics of population systems. In this paper, the dynamics of multiregional populations are analyzed when occasional perturbations resulting from changes in social and economic conditions exist. A perturbation theory for population models is introduced and the increasing effect of changes in demographic rates in determining the spatial component of the multiregional population growth is shown." The author outlines the critical situations in which perturbations produce drastic demographic changes. Data for Italy are used to show the theory's usefulness in analyzing both short- and long-term effects of changes in vital rates.     

Tackling Informality: Why HIV/AIDS Needs to be a Critical Component of Urban Development Policies

Cities in the South are faced with the double challenges of underdevelopment and poverty on the one hand and urbanisation on the other. As the developing regions of the South continue to urbanise at an incredible rate, it is clear that many cities do not have the necessary capacity to respond to the increasing needs and demands by urban residents. As a result, many new city residents have no other option but to settle in informal areas. These areas have long been associated with poor and unhealthy living conditions and, more recently, the links between these living conditions and HIV/AIDS have become increasingly clear. Research suggests that developmental factors like poverty, unemployment, gender inequality and inadequate shelter, water and sanitation all play a role in increasing vulnerability to HIV/AIDS. These conditions further affect the ability of HIV-positive individuals, households and communities to cope with the consequences of the epidemic. This in turn leads to further impoverishment and reduces the likelihood that people living in informal settlements will be able to improve their livelihoods. Yet, little attention has been paid by policy makers and planners to the relationship between HIV/AIDS and informality despite the challenge it provides for cities and the implications of the epidemic for government institutions and local government in particular. This paper argues that informality is complex and that its heterogeneous nature is not effectively understood and thus not given appropriate recognition and support. It looks at the effects of the HIV/AIDS epidemic within this context of informality and the inevitable wave of urbanisation. The paper suggests that the only way to deal effectively with HIV/AIDS (and informality) is through planning and building integrated and sustainable urban settlements that respond to the complexities of informality in cities of the developing world.     

Spatial-dynamic population systems: analysis and projection

"In this paper a set of more-detailed multiregional population accounts is proposed to specify more realistically the exposure time of populations at risk for various components of population change. The concepts of population-time at risk and forward demographic rates based on the initial population are discussed. The relations of the forward demographic rates defined in this paper with the occurrence-exposure demographic rates are discussed. A more precise and straightforward multiregional population model is developed on the basis of forward demographic rates. The model is also expressed in the familiar matrix form of multiregional, cohort-survival models." Some applications of the model are made to data for China.     

Source region effects in epidemic disease modeling: Comparisons between influenza and HIV

The research reported in this paper presents the preliminary findings obtained from applying a multiregion disease model to forecasting pandemics of infectious disease. The beginning section examines the structure of the modeling system together with various start region effects that are embedded in the framework. An appropriate form of the model is fitted to the known spread of the 1957 Asian influenza pandemic and then used to examine the distributions of warning times that are associated with varying the location of the source region. The disease parameters are adjusted to represent current knowledge about the host-agent relationship for HIV, and used to make povisional forecast for the spread of the virus during the next half century. The discussion considers how this highly simplified simulation procedure might be improved upon in future work, particularly in relation to cross-infection between the high risk groups.     

THE ESTIMATION AND APPLICATION OF MULTI-REGIONAL ECONOMIC PLANNING MODELS USING DATA ENVELOPMENT ANALYSIS

ABSTRACT This paper is concerned primarily with the problems of estimating the production possibility parameters of multiregional economic planning models of a mathematical programming form. It reviews and illustrates a technique known as Data Envelopment Analysis (DEA) and examines the application of this technique to the problem of production function estimation. The standard use of DEA for measuring relative efficiencies of production units is noted. A method for generating input demand and output supply functions using data envelope parameters is presented. Some comments are made about the 'missing facet problem', which effects this method's reliability, and a procedure for avoiding the problem is outlined. An alternative approach to supply and demand function estimation based on activity coefficient data is described. Two methods for measuring the relative effectiveness of production units are also presented. Finally, a strategy for using DEA to provide a streamlined activity analysis coefficient matrix for multiregional economic planning models is suggested, and some questions on the practical application and theoretical applicability of DEA-estimated models are considered.     

An integrated approach for tactical monitoring and data-driven spread forecasting of wildfires

In recent times there have been increasing efforts to integrate technology into wildfire management, especially in the fields of tactical monitoring and simulation. On the one hand, thermal infrared imaging (TIR) systems have been installed aboard surveillance aircraft including unmanned systems (UAS). On the other, there exists a variety of models and simulators able to forecast the fire spread. However, both fields currently present significant limitations. While relevant information is still extracted manually from aerial thermal imagery and is most times merely qualitative, simulators’ accuracy on fire spread prediction has proved insufficient. To solve these issues, this article presents a twofold methodology to couple meaningful automated wildfire monitoring with accurate fire spread forecasting. The main goals are to, firstly, automatically process aerial TIR imagery so that valuable information can be produced in real time during the event and, secondly, use this information to adjust a Rothermel-based simulator in order to improve its accuracy on-line. The fire perimeter location is tracked automatically through an unsupervised edge detector. Afterwards, an assimilation module uses the remotely sensed data to optimise the simulator's fuel and wind parameters, which are assumed to remain constant for a certain period of time. Subsequently, the optimum parameters’ values are used to issue a fire evolution forecast. All outputs are projected onto the corresponding Digital Terrain Model (DTM) and integrated into a Geographic Information System (GIS) for visualization. The global system was validated using two large-scale experiments. If these algorithms can be applied to a sufficiently rich and varied set of experimental data and further developed to cope with more complex scenarios, they could eventually be incorporated into a fire management decision support system.     

Soft computing for solar radiation potential assessment in Algeria

ABSTRACT

Precise estimation of solar radiation is a highly required parameter for the design and assessment of solar energy applications. Over the past years, many machine learning techniques have been proposed in order to improve the forecasting performance using different input attributes. The aim of this study is the forecasting of one day ahead of horizontal global solar radiation using a set of meteorological and geographical inputs. In this respect, the Gaussian process regression methodology (GPR) and least-square support vector machine (LS-SVM) with different kernels are evaluated in order to select the most appropriate forecasting model. In order to assess the proposed models, the southern Algerian city, Ghardaia regions, was selected for this study. A historical data of five years (2013–2017) of meteorological data collected at Renewable Energies (URAER) in Ghardaia city are used. The achieved results demonstrate that all the proposed models give approximately similar results in terms of statistical indicators. In term of processing time, all the models showed acceptable computational efficiency with less computational costs of the GPR model among all machine learning models.     

高密度城市的多尺度空间防疫体系建构思考

自城市诞生以来,与疾病和灾害的斗争,一直都是城市规划建设提升的主要动因之一,尤其在当代社会人口、信息、经济等高频交互的背景下,高密度城市成为疫病快速传播影响的重要因素。本文阐述了新世纪全球疫病在高密度城市传播的特征和我国城市防疫中的城市规划建设问题,提出建构包括城市-社区-建筑的多尺度空间防疫体系,并以综合大数据的智能化平台监控、反演和预警疫病爆发与传播情况。     

Finite element modelling and field validation of prestressed concrete sleepers and fastening systems

Prestressed concrete sleepers and elastic fastening systems have been widely applied in North America to accommodate increased freight axle loading and the development of high-speed passenger rail systems. However, the design standard of the American Railway Engineering and Maintenance-of-Way Association remains unclear about the relationship between some critical design parameters and the vertical and lateral load paths through the track structure. In this study, field experimentation is conducted at the Transportation Technology Center in Pueblo, CO, and the test data are compared with finite element (FE) models of the track structure for model validation. Strain gauges and potentiometers are installed in the field to measure the response of concrete sleepers and fastening systems. The FE models consist of two parts: a detailed single-sleeper model to capture the local response of the loaded rail seat, and a global multi-sleeper model to provide realistic boundary conditions for the detailed model. The bond–slip behaviour between concrete and prestressing wires, and inelastic material properties are incorporated in the FE models. Good agreement is observed between the test measurement and the model output. The validated FE model is used for parametric studies on the some critical design parameters, and conclusions about the load path through the sleepers and fastening systems are summarised.     

Short-term forecasting of internal migration

A new methodological approach to the forecasting of short-term trends in internal migration in the United States is introduced. "Panel-data (or longitudinal-data) models are used to represent the relationship between destination-specific out-migration and several explanatory variables. The introduction of this methodology into the migration literature is possible because of some new and improved databases developed by the U.S. Bureau of the Census.... Data from the Bureau of Economic Analysis are used to investigate the incorporation of exogenous factors as variables in the model." The exogenous factors considered include employment and unemployment, income, population size of state, and distance between states. The author concludes that "when one...includes additional parameters that are estimable in longitudinal-data models, it turns out that there is little additional information in the exogenous factors that is useful for forecasting."     

Core–periphery dynamics in the Portland, Oregon, region: 1982–2006

The relative strength of positive and negative spillovers of urban development is a long-standing and contested issue in regional and development economics, and the search for spread and backwash effects of development in urban core economies goes back at least 50 years. Using data from IMPLAN and the Bureau of Economic Analysis to develop multiregional input–output models, we developed estimates of core–periphery economic interdependence (sales and purchases of goods and services and commuting of workers between the core and the periphery) of the Portland, Oregon, region for 1982 and 2006. We explored whether the changing flows of sales and purchases, spillovers and commuting between 1982 and 2006 suggested a dominance of spread effects or backwash effects. We found increased commuting between periphery and core, decreased core–periphery transactions, and smaller core-to-periphery spillovers and periphery-to-core spillovers in both goods and services. Our findings do not point to a clear dominance of spread or backwash effects. Results showing smaller core-to-periphery and periphery-to-core multipliers/spillovers suggest that spread effects related to trade in goods and services weakened between 1982 and 2006. Our findings of increased commuting are consistent with enhanced spread effects in labor markets.     

Major fire spread in a tunnel with water mist: A theoretical model

A model of the effect of water mist on major fire spread in a tunnel is described. It employs the concepts of non-linear dynamical systems theory and identifies the onset of instability with major fire spread in a tunnel. The purpose is to identify the thermo-physical and geometrical conditions which lead to instability and sudden fire spread. It uses as a starting point one of the non-linear models for major fire spread which have been developed by the author over many years and assumes that a water mist system operates.The case considered assumes the existence of a longitudinal forced ventilation and predicts the critical heat release rate needed for a fire to spread from an initial fire to an item with a given assumed shape; in the presence of water mist. There is assumed to be no flame impingement on the target object. The target object may be taken to approximate a vehicle. The illustrative case approximating fire spread from an initial fire to a heavy goods vehicle (HGV) is presented; it is not restricted to this case, however. The model is being identified with the name FIRE-SPRINT C1, which is an acronym of Fire Spread in Tunnels, Model C, Version 1. It has been developed from an earlier model, FIRE-SPRINT A3 and considers a case where, in the absence of a fire fighting system, there is the potential for a major fire.     

Guidelines for effective workplace HIV/AIDS intervention management by construction firms

Construction firms have an important role in combating HIV/AIDS in the South African construction industry. The HIV/AIDS intervention management practices of 12 construction firms in Cape Town are examined through interviews and documents. From thematic analysis, five themes emerged: construction firms’ perceptions of HIV/AIDS as a threat to the firm; construction firm interventions; barriers to the success of interventions; the role of service providers; and state-led interventions. A tension exists in managing HIV/AIDS interventions as firms are concerned with productivity and profit maximization, but are becoming more engaged with corporate social responsibility and a higher duty of care towards employees. Interventions should extend beyond awareness and prevention campaigns to include testing and treatment programmes. A guideline checklist for such interventions is proposed. Partnering with specialized service providers is recommended, as well as engaging closely with public sector services. Firms successfully managing their HIV/AIDS response should share their experience with others struggling to respond. Employee issues of stigma and reluctance to disclose need to be addressed. Attention should be paid to the employment structure of the construction industry and to the needs of the informal sector.     

高层建筑结构刚度退化模态分析与灰色预测研究

在高层建筑中 ,结构柱刚度的退化对结构的模态会产生一定程度的影响 ,本文应用ANSYS软件对结构在不同刚度退化情况下进行了模态分析 ,研究了结构特征频率随刚度退化位置和程度等变化的关系及趋势 ;运用灰色理论对计算结果进行了预测分析 ,建立了刚度退化的预测模型 ,计算表明本模型是有效的     

Assessment of predictive uncertainty within the framework of water demand forecasting using the Model Conditional Processor (MCP)

This paper presents an application of the Model Conditional Processor (MCP), originally proposed by Todini (2008) within the hydrological framework, to assess the predictive uncertainty in water demand forecasting related to water distribution systems. The MCP enables us to assess the probability distribution of the future water demand conditional on the forecasts provided by two or more deterministic forecasting models. In the numerical application described here, where two years of hourly water demand data for a town in northern Italy are considered, two forecasting models are applied in order to forecast hourly water demands from 1 to 24 hours ahead: the first model has a modular structure comprising a periodic component which reflects the long-term effects and a persistence component which represents the short-term memory of the process; the latter is based on neural networks. The results highlight the effectiveness of the approach, provided that the data set used for the MCP parameterization is properly selected so as to be actually representative of the accuracy of the real-time water demand forecasting models.     

Nonlinear Analysis of Structural Frame Systems by the State-Space Approach

This article presents the formulation and solution of the equations of motion for distributed parameter nonlinear structural systems in state space. The essence of the state-space approach (SSA) is to formulate the behavior of nonlinear structural elements by differential equations involving a set of variables that describe the state of each element and to solve them in time simultaneously with the global equations of motion. The global second-order differential equations of dynamic equilibrium are reduced to first-order systems by using the generalized displacements and velocities of nodal degrees of freedom as global state variables. In this framework, the existence of a global stiffness matrix and its update in nonlinear behavior, a cornerstone of the conventional analysis procedures, become unnecessary as means of representing the nodal restoring forces. The proposed formulation overcomes the limitations on the use of state-space models for both static and dynamic systems with quasi-static degrees of freedom. The differential algebraic equations (DAE) of the system are integrated by special methods that have become available in recent years. The nonlinear behavior of structural elements is formulated using a flexibility-based beam macro element with spread plasticity developed in the framework of state-space solutions. The macro-element formulation is based on force-interpolation functions and an intrinsic time constitutive macro model. The integrated system including multiple elements is assembled, and a numerical example is used to illustrate the response of a simple structure subjected to quasi-static and dynamic-type excitations. The results offer convincing evidence of the potential of performing nonlinear frame analyses using the state-space approach as an alternative to conventional methods.     

Large metropolitan water demand forecasting using DAN2, FTDNN,and KNN models: A case study of the city of Tehran,Iran

Efficient operation of urban water systems necessitates accurate water demand forecasting. We present daily, weekly, and monthly water demand forecasting using dynamic artificial neural network (DAN2), focused time-delay neural network (FTDNN), and K-nearest neighbor (KNN) models for the city of Tehran. The daily model investigates whether partitioning weekdays into weekends and non-weekends can improve forecast results; it did not. The weekly model yielded good results by using the summation of the daily forecast values into their corresponding weeks. The monthly results showed that partitioning the year into high and low seasons can improve forecast accuracy. All three models offer very good results for water demand forecasting. DAN2, the best model, yielded forecasting accuracies of 96%, 99%, and 98%, for daily, weekly, and monthly models respectively.     

A new method of ozone forecasting using fuzzy expert and neural network systems

This study describes the method of forecasting daily maximum ozone concentrations at four monitoring sites in Seoul, Korea. The forecasting tools developed are fuzzy expert and neural network systems. The hourly data for air pollutants and meteorological variables, obtained both at the surface and at the high elevation (500 hPa) stations of Seoul City for the period of 1989-1999, were analyzed. Two types of forecast models are developed. The first model, Part I, uses a fuzzy expert system and forecasts the possibility of high ozone levels (equal to or above 80 ppb) occurring on the next day. The second model, Part II, uses a neural network system to forecast the daily maximum concentration of ozone on the following day. The forecasting system includes a correction function so that the existing model can be updated whenever a new ozone episode appears. The accuracy of the forecasting system has been improved continuously through verification and augmentation.     

An integrated model of HIV/AIDS testing behaviour in the construction industry

The South African construction industry is one of the economic sectors most adversely affected by the HIV/AIDS pandemic. Prevalence rates exceed those of most other sectors. Little is known about the antibody testing behaviour of construction workers, and the determinants thereof. A field-administered questionnaire survey, using an item catalogue based on similar surveys, gathered data from 512 site-based construction employees in the Western Cape, South Africa. An integrated hypothesized conceptual model of testing behaviour, derived from the literature, was proposed as a starting point for data analysis. This model comprising demographic factors, lifestyle risk and condom use, alcohol consumption, drug use, knowledge about HIV/AIDS, prejudice towards HIV+ persons, and attitudinal fear of being tested, was used to explain testing behaviour. Bivariate analysis, regression modelling, and structural equation modelling were then used to test the conceptual model. A revised model was proposed. The findings indicate that: (1) employment type, alcohol consumption, drug use, and HIV/AIDS knowledge are the terminal predictors of testing behaviour; (2) knowledge about the disease is determined by education level and ethnicity; (3) age, gender, ethnicity and education behave as significant predictors of alcohol consumption; (4) drug use is predicted by employment type, education and alcohol consumption (marginally); and (5) the interrelationship between knowledge, prejudice, and fear of being tested is nuanced and complex. In strategies for positively influencing employee testing behaviour, employers should first ensure that effective communication is established with workers in all employment categories. Interventions relating to alcohol consumption and drug use by employees need particular attention. Existing peer educator training, and awareness campaign media, should be particularly sensitive to ethnic and cultural values that are likely to influence HIV/AIDS testing behaviour.