Territorial Intelligence of Vulnerability Systems 2- Sustainable Modelling of Globalization Challenge

Globalization as progress of economic development has increased population socioeconomical vulnerability when unequal wealth distribution within economic development process constitutes the main rule, with widening the gap between rich and poors by environmental pricing. Econological vulnerability is therefore increasing too, as dangerous substance and techniques should produce polluted effluents and industrial or climatic risk increasing (Woloszyn, Quenault, Faburel, 2012). To illustrate and model this process, we propose to introduce an analogical induction-model to describe both vulnerability situations and associated resilience procedures. At this aim, we first develop a well-known late 80?s model of socio-economic crack-up, known as 'Silent Weapons for Quiet Wars', which presents economics as a social extension of natural energy systems. This last, also named 'E-model', is constituted by three passive components, potential energy, kinetic energy, and energy dissipation, thus allowing economical data to be treated as a thermodynamical system. To extend this model to social and ecological sustainability pillars, we propose to built an extended E(Economic)-S(Social)-O(Organic) model, based on the three previous components, as an open model considering feedbacks as evolution sources. An applicative illustration of this model will then be described, through this summer's american severe drought event analysis

Territorial Intelligence of Vulnerability Systems 2- Sustainable Modelling of Globalization Challenge

Globalization as progress of economic development has increased population socioeconomical vulnerability when unequal wealth distribution within economic development process constitutes the main rule, with widening the gap between rich and poors by environmental pricing. Econological vulnerability is therefore increasing too, as dangerous substance and techniques should produce polluted effluents and industrial or climatic risk increasing (Woloszyn, Quenault, Faburel, 2012). To illustrate and model this process, we propose to introduce an analogical induction-model to describe both vulnerability situations and associated resilience procedures. At this aim, we first develop a well-known late 80?s model of socio-economic crack-up, known as 'Silent Weapons for Quiet Wars', which presents economics as a social extension of natural energy systems. This last, also named 'E-model', is constituted by three passive components, potential energy, kinetic energy, and energy dissipation, thus allowing economical data to be treated as a thermodynamical system. To extend this model to social and ecological sustainability pillars, we propose to built an extended E(Economic)-S(Social)-O(Organic) model, based on the three previous components, as an open model considering feedbacks as evolution sources. An applicative illustration of this model will then be described, through this summer's american severe drought event analysis

Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change

The integration of scientific knowledge about possible climate change impacts on water resources has a direct implication on the way water policies are being implemented and evolving. This is particularly true regarding various technical steps embedded into the EU Water Framework Directive river basin management planning, such as risk characterisation, monitoring, design and implementation of action programmes and evaluation of the "good status" objective achievements (in 2015). The need to incorporate climate change considerations into the implementation of EU water policy is currently discussed with a wide range of experts and stakeholders at EU level. Research trends are also on-going, striving to support policy developments and examining how scientific findings and recommendations could be best taken on board by policy-makers and water managers within the forthcoming years. This paper provides a snapshot of policy discussions about climate change in the context of the WFD river basin management planning and specific advancements of related EU-funded research projects. Perspectives for strengthening links among the scientific and policy-making communities in this area are also highlighted.

Novel Negotiation protocol to support CDM process in a layered ATM System

In the SESAR Step 2 concept of operations a RBT is available and seen by all making it possible to conceive a different operating method than the current ATM system based on Collaborative Decisions Making processes. Currently there is a need to describe in more detail the mechanisms by which actors (ATC, Network Management, Flight Crew, airports and Airline Operation Centre) will negotiate revisions to the RBT. This paper introduces a negotiation model, which uses constraint based programing applied to a mediator to facilitate negotiation process in a SWIM enabled environment. Three processes for modelling the negotiation process are explained as well a preliminary reasoning agent algorithm modelled with constraint satisfaction problem is presented. Computational capability of the model is evaluated in the conclusion.

Modelling the relationship between urban environment and travel behaviour: policy and indicators

Due to the necessity to undertake activities, every year people increase their standards of travelling (distance and time). Urban sprawl development plays an important role in these "enlargements". Thus, governments invest money in an exhaustiva search for solutions to high levels of congestion and car-trips. The complex relationship between urban environment and travel behaviour has been studied in a number of cases. Thus, the objective of this paper is to answer the important question of which land-use attributes influence which dimensions of travel behaviour, and to verify to what extent specific urban planning measures affect the individual decision process, by exhaustiva statistical and systematic tests. This paper found that a crucial issue in the analysis of the relationship between the built environment and travel behaviour is the definition of indicators. As such, we recommend a feasible list of indicators to analyze this relationship.

Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.

Implementation Feasibility of a Digital Nervous System for the Construction Industry: For Efficient and Effective Information Management across the Project Lifecycle

The construction industry has long been considered as highly fragmented and non-collaborative industry. This fragmentation sprouted from complex and unstructured traditional coordination processes and information exchanges amongst all parties involved in a construction project. This nature coupled with risk and uncertainty has pushed clients and their supply chain to search for new ways of improving their business process to deliver better quality and high performing product. This research will closely investigate the need to implement a Digital Nervous System (DNS), analogous to a biological nervous system, on the flow and management of digital information across the project lifecycle. This will be through direct examination of the key processes and information produced in a construction project and how a DNS can provide a well-integrated flow of digital information throughout the project lifecycle. This research will also investigate how a DNS can create a tight digital feedback loop that enables the organisation to sense, react and adapt to changing project conditions. A Digital Nervous System is a digital infrastructure that provides a well-integrated flow of digital information to the right part of the organisation at the right time. It provides the organisation with the relevant and up-to-date information it needs, for critical project issues, to aid in near real-time decision-making. Previous literature review and survey questionnaires were used in this research to collect and analyse data about information management problems of the industry – e.g. disruption and discontinuity of digital information flow due to interoperability issues, disintegration/fragmentation of the adopted digital solutions and paper-based transactions. Results analysis revealed efficient and effective information management requires the creation and implementation of a DNS.

Modelling a biomass supply chain through discrete-event simulation

The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided

Modelling the effect of shear history on activated sludge flocculation

The aim of this paper is to investigate the effect of shear history on activated sludge flocculation dynamics and to model the observed relationships using population balances. Activated sludge flocs are exposed to dramatic changes in the shear rate within the treatment process, as they pass through localised high and low mixing intensities within the aeration basin and are cycled through the different unit operations of the treatment process. We will show that shear history is a key factor in determining floc size, and that the floc size varies irreversibly with changes in shear rate. A population balance model of the flocculation process is also introduced and evaluated.

Simulation modelling applied to runoff modelling using mapscript

Dynamic spatial analysis addresses computational aspects of space–time processing. This paper describes the development of a spatial analysis tool and modelling framework that together offer a solution for simulating landscape processes. A better approach to integrating landscape spatial analysis with Geographical Information Systems is advocated in this paper. Enhancements include special spatial operators and map algebra language constructs to handle dispersal and advective flows over landscape surfaces. These functional components to landscape modelling are developed in a modular way and are linked together in a modelling framework that performs dynamic simulation. The concepts and modelling framework are demonstrated using a hydrological modelling example. The approach provides a modelling environment for scientists and land resource managers to write and to visualize spatial process models with ease.

Extinction times for a general birth, death and catastrophe process

The birth, death and catastrophe process is an extension of the birth-death process that incorporates the possibility of reductions in population of arbitrary size. We will consider a general form of this model in which the transition rates are allowed to depend on the current population size in an arbitrary manner. The linear case, where the transition rates are proportional to current population size, has been studied extensively. In particular, extinction probabilities, the expected time to extinction, and the distribution of the population size conditional on nonextinction (the quasi-stationary distribution) have all been evaluated explicitly. However, whilst these characteristics are of interest in the modelling and management of populations, processes with linear rate coefficients represent only a very limited class of models. We address this limitation by allowing for a wider range of catastrophic events. Despite this generalisation, explicit expressions can still be found for the expected extinction times.

Process, performance, and pollution potential: A review of septic tank-soil absorption systems

On-site wastewater treatment and dispersal systems (OWTS) are used in non-sewered populated areas in Australia to treat and dispose of household wastewater. The most common OWTS in Australia is the septic tank-soil absorption system (SAS) - which relies on the soil to treat and disperse effluent. The mechanisms governing purification and hydraulic performance of a SAS are complex and have been shown to be highly influenced by the biological zone (biomat) which develops on the soil surface within the trench or bed. Studies suggest that removal mechanisms in the biomat zone, primarily adsorption and filtering, are important processes in the overall purification abilities of a SAS. There is growing concern that poorly functioning OWTS are impacting upon the environment, although to date, only a few investigations have been able to demonstrate pollution of waterways by on-site systems. In this paper we review some key hydrological and biogeochemical mechanisms in SAS, and the processes leading to hydraulic failure. The nutrient and pathogen removal efficiencies in soil absorption systems are also reviewed, and a critical discussion of the evidence of failure and environmental and public health impacts arising from SAS operation is presented. Future research areas identified from the review include the interactions between hydraulic and treatment mechanisms, and the biomat and sub-biomat zone gas composition and its role in effluent treatment.

Modelling knowledge production performance of research centres with a focus on triple bottom line benchmarking

We demonstrate a portable process for developing a triple bottom line model to measure the knowledge production performance of individual research centres. For the first time, this study also empirically illustrates how a fully units-invariant model of Data Envelopment Analysis (DEA) can be used to measure the relative efficiency of research centres by capturing the interaction amongst a common set of multiple inputs and outputs. This study is particularly timely given the increasing transparency required by governments and industries that fund research activities. The process highlights the links between organisational objectives, desired outcomes and outputs while the emerging performance model represents an executive managerial view. This study brings consistency to current measures that often rely on ratios and univariate analyses that are not otherwise conducive to relative performance analysis.

Cognitive change process during group cognitive behaviour therapy for depression

Background: This study extended that of Kwon and Oei [Kwon, S.M., Oei, T.P.S., 2003. Cognitive change processes in a group cognitive behavior therapy of depression. J. Behav. Ther. Exp. Psychiatry, 3, 73-85], which outlined a number of testable models based on Beck's cognitive theory of depression. Specifically, the current study tested the following four competing models: the causal, consequential, fully and partially interactive cognitive models in patients with major depressive disorder. Methods: A total of 168 clinically depressed outpatients were recruited into a 12-week group cognitive behaviour therapy program. Data was collected at three time points: baseline, mid- and at termination of therapy using the ATQ DAS and BD1. The data were analysed with Amos 4.01 (Arbuckle, J.L., 1999. Amos 4.1. Smallwaters, Chicago.) structural equation modelling. Results: Results indicated that dysfunctional attitudes, negative automatic thoughts and symptoms of depression reduced significantly during treatment. Both the causal and consequential models equally provided an adequate fit to the data. The fully interactive model provided the best fit. However, after removing non-significant pathways, it was found that reduced depressive symptom contributed to reduced depressogenic automatic thoughts and dysfunctional attitudes, not the reverse. Conclusion: These findings did not fully support Beck's cognitive theory of depression that cognitions are primary in the reduction of depressed mood. (c) 2006 Elsevier B.V. All rights reserved.