A new approach to testing an integrated water systems model using qualitative scenarios

Integrated systems models have been developed over decades, aiming to support the decision-makers in the planning and managing of natural resources. The inherent model complexity, lack of knowledge about the linkages among model components, scarcity of field data, and uncertainty involved with internal and external factors of the real system call their practical usefulness into doubt. Validation tests designed for such models are just immature, and are argued to have some characteristics that differ from the ones used for validating other types of models. A new approach for testing integrated water systems models is proposed, and applied to test the RaMCo model. Expert knowledge is elicited in the form of qualitative scenarios and translated into quantitative projections using fuzzy set theory. Trend line comparison of the projections made by the RaMCO model and the qualitative projections based on expert knowledge revealed an insufficient number of land-use types adopted by the RaMCo model. This insufficiency makes the model inadequate to describe the consequences of the changes in socio-economic factors and policy options on the erosion from the catchment and the sediment yields at the inlet of a storage lake.     

Optimal uncertainty reduction for multi-disciplinary multi-output systems using sensitivity analysis

We present a sensitivity analysis based uncertainty reduction approach, called Multi-dIsciplinary Multi-Output Sensitivity Analysis (MIMOSA), for the analysis model of a multi-disciplinary engineering system decomposed into multiple subsystems with each subsystem analysis having multiple inputs with reducible uncertainty and multiple outputs. MIMOSA can determine: (1) the sensitivity of system and subsystem outputs to input uncertainties at both system and subsystem levels, (2) the sensitivity of the system outputs to the variation from subsystem outputs, and (3) the optimal “investment” required to reduce uncertainty in inputs in order to obtain a maximum reduction in output variations at both the system and subsystem levels. A numerical and an engineering example with two and three subsystems, respectively, have been used to demonstrate the applicability of the MIMOSA approach.     

Fuzzy parametric programming model for multi-objective integrated solid waste management under uncertainty

Solid waste management is increasingly becoming a challenging task for the municipal authorities due to increasing waste quantities, changing waste composition, decreasing land availability for waste disposal sites and increasing awareness about the environmental risk associated with the waste management facilities. The present study focuses on the optimum selection of the treatment and disposal facilities, their capacity planning and waste allocation under uncertainty associated with the long-term planning for solid waste management. The fuzzy parametric programming model is based on a multi-objective, multi-period system for integrated planning for solid waste management. The model dynamically locates the facilities and allocates the waste considering fuzzy waste quantity and capacity of waste management facility. The model addresses uncertainty in waste quantity as well as uncertainties in the operating capacities of waste management facilities simultaneously. It was observed that uncertainty in waste quantity is likely to affect the planning for waste treatment/disposal facilities more as compared with the uncertainty in the capacities of the waste management facilities. The relationship between increase in waste quantity and increase in the total cost/risk involved in waste management is found to be nonlinear. Therefore, it is possible that a marginal change in waste quantity could increase the total cost/risk substantially. The information obtained from the analysis of modeling results can be effectively used for understanding the effect of changing the priorities and objectives of planning decisions on facility selections and waste diversions.     

Control-oriented model for integrated diesel engine and aftertreatment systems thermal management

In order to perform effective real-time active thermal management, control-oriented thermal models for the integrated Diesel engine and aftertreatment systems are required. The purpose of this study is to develop a control-oriented temperature dynamic model for a modern Diesel engine equipped with a complete set of aftertreatment systems including Diesel oxidation catalyst (DOC), Diesel particulate filter (DPF), and urea-based selective catalytic reduction (SCR) system. In specific, the influences of in-cylinder post injection (fuel injection rate and injection timing) on the temperature dynamics were investigated. Several engine experiments were conducted to validate the proposed model in various operating scenarios. Experimental results show that the developed model can well capture the thermal behaviors of the aftertreatment systems with and without post injections.     

The zone plate as an aid to testing display systems

The zone plate pattern is a two dimensional linear sweep which is able to test a television system's vertical as well as its horizontal frequency characteristic. The circular form has been used for some time but the hyperbolic form is becoming increasingly useful. The pattern can test any situation where frequency shapping, sampling or modulation is involved such as filter characteristics, source and display characteristics, sub-Nyquist sampling system impairments and PAL coding impairments. The pattern can be generated electronically in both circular and hyperbolic form, although the latter is simpler.     

Computer-based interface for an integrated solid waste management optimization model

Planning a regional waste management strategy is a critical step that, if not properly addressed, will lead to an inefficient integrated solid waste management (ISWM) system. Regional planning affects the design, implementation, and efficiency of the overall ISWM scheme. Consequently, decision-makers must look for optimized regional waste management planning to achieve a successful strategy. The optimization of an ISWM strategy for an area requires the knowledge of available solid waste management alternatives and technologies, economic and environmental costs associated with these alternatives, and their applicability to the specific area. Decision-makers often have to rely on optimization models to examine the impacts of mass balance, capacity limitations, operation, and site availability as well as to analyze different alternative options in the selection of a cost effective, environmentally sound waste management alternative. In this context, the complexity associated with the formulation of optimization models may hinder its use, and consequently, user friendliness is a major concern. This paper presents an interface that was developed to address this concern, that is to formulate the matrices associated with an integrated waste management optimization model.     

Validation of an evaluation model for learning management systems

Abstract   This study aims to validate a model for evaluating learning management systems (LMS) used in e-learning fields. A survey of 163 e-learning experts, regarding 81 validation items developed through literature review, was used to ascertain the importance of the criteria. A concise list of explanatory constructs, including two principle factors, was extracted from the responses of 133 respondents by exploratory factor analysis. Factor I was labeled as 'instruction management, screen design, and technology' and factor II, 'interaction and evaluation'. Factors I and II consisted of four and three sub-factors, respectively. Confirmatory factor analysis, in turn, was carried out to assess the degree to which the plausibility of factor models was empirically confirmed. Overall fit measures (RMSEA, CFI, NNFI indexes) showed the model to be quite suitable for LMS evaluation. Reliability estimates using Cronbach's alpha indicated that the evaluation tool had good internal consistency. The overall results of the analyses suggest that this evaluation tool is highly instrumental for LMS.     

Systematic testing: A means for validating reactive systems

The validity of the first (formal) model of a system to be developed is crucial for the whole development process. Systematically checking this validity helps avoid costs that could arise if it were discovered too late that the system does not satisfy the customer's needs and expectations. This paper addresses how to validate synchronous reactive programs using the technique of systematic testing. Testing reactive systems differs from testing sequential systems: instead of checking simple pairs of inputs and outputs, sequences of inputs and outputs have to be checked. Thus, testing cannot be based on a simple function model, mapping input values onto output values nor on a control flow graph model (where a path from the start node to the final node represents one execution through the represented program). The model widely used instead is that of a finite-state machine. A systematic testing approach is presented that is both effective and efficient for validating reactive systems. It uses an additional specification based on a finite-state machine model. The approach is demonstrated for the well-known lift example. It is shown how to use the specification for carefully choosing a set of test criteria that address different types of fault; a procedure for selecting test cases and test data that satisfy the chosen criteria is presented.     

System-level integrated power management for handheld systems

We propose a system-level integrated power management scheme for battery-operated handheld systems such as cell phones and PDAs. Rather than dealing separately with each system component, we consider the interactions between CPU, WNIC (wireless network interface card), LCD, and applications, to reduce energy consumption at the system-level. Depending on the type of applications, the proposed scheme takes the interaction between CPU voltage and frequency and either LCD clock frequency or WNIC power modes, selectively, or both of them. The proposed method selects voltage for CPU in the context of LCD clock speed to reduce the system energy consumption. The application type and the power mode of WNIC are also considered to control the CPU voltage and frequency. Experimental results show that our scheme reduces the system energy consumption by as much as 30% compared to the systems of simply combining DVS (dynamic voltage scaling) and DPM (dynamic power management) or those of using no energy saving policy.     

Multivariate significance testing and model calibration under uncertainty

The importance of modeling and simulation in the scientific community has drawn interest towards methods for assessing the accuracy and uncertainty associated with such models. This paper addresses the validation and calibration of computer simulations using the thermal challenge problem developed at Sandia National Laboratories for illustration. The objectives of the challenge problem are to use hypothetical experimental data to validate a given model, and then to use the model to make predictions in an untested domain. With regards to assessing the accuracy of the given model (validation), we illustrate the use of Hotelling’s T² statistic for multivariate significance testing, with emphasis on the formulation and interpretation of such an analysis for validation assessment. In order to use the model for prediction, we next employ the Bayesian calibration method introduced by Kennedy and O’Hagan. Towards this end, we discuss how inherent variability can be reconciled with “lack-of-knowledge” and other uncertainties, and we illustrate a procedure that allows probability distribution characterization uncertainty to be included in the overall uncertainty analysis of the Bayesian calibration process.     

Decision support system development for integrated management of European coastal lagoons

In this paper, a general framework for the development of Decision Support Systems (DSSs) for the management of coastal lagoons is presented. The proposed DSS structure integrates the information provided by several models accounting for different characteristics of lagoon ecosystems, including biogeochemical, hydrodynamic, ecological and socio-economic aspects. Outputs and indicators provided by the models are used to accomplish the decision task by the application of multicriteria analysis. Model uncertainty and robustness with respect to uncontrollable factors are addressed. Application of the proposed DSS structure to five lagoons located in the Mediterranean area is discussed, with special focus on the management of clam farming in the Sacca di Goro lagoon (Italy). Thanks to its flexibility, the proposed DSS structure is also applicable in decision problems arising in different fields.     

MPC for stable linear systems with model uncertainty

In this paper, we developed a model predictive controller, which is robust to model uncertainty. Systems with stable dynamics are treated. The paper is mainly focused on the output-tracking problem of a system with unknown steady state. The controller is based on a state-space model in which the output is represented as a continuous function of time. Taking advantage of this particular model form, the cost functions is defined in terms of the integral of the output error along an infinite prediction horizon. The model states are assumed perfectly known at each sampling instant (state feedback). The controller is robust for two classes of model uncertainty: the multi-model plant and polytopic input matrix. Simulations examples demonstrate that the approach can be useful for practical application.     

Flow and solute fluxes in integrated wetland and coastal systems

Details are given of an experimental study of the flow and tracer transport processes in an integrated wetland and coastal basin. A novel physical model was constructed to enable observations and measurements to be made of groundwater transport through a sand embankment between a wetland and coastal area. This was an idealised scale model of the West Fleet Lagoon, Chesil Beach and the adjacent coastal waters, located in Dorset, UK. An extensive set of data of the seepage fluxes through the embankment was collected by monitoring the varying water level and velocity distributions on both sides of the embankment. The transport behaviour of a conservative tracer was also studied for a constant water level on the wetland side of the embankment, while running a continuous tide on the coastal side. Time series pictures of the concentration distributions of the tracer were filmed using a digital camcorder. An integrated surface and groundwater numerical model was also used in this study to assist in the analysis, with the numerical model predictions being compared with the images recorded from the experiments. Details of the physical model, experimental procedures and the equipment used in the study are reported in this paper.     

Untangling drivers of species distributions: Global sensitivity and uncertainty analyses of MaxEnt

Untangling drivers of systems and uncertainty for species distribution models (SDMs) is important to provide reliable predictions that are useful for conservation campaigns. This is particularly true for species whose habitat is threatened by climate change that enhances the uncertainty in future species distributions. Global sensitivity and uncertainty analyses (GSUA) is a robust method to globally investigate the uncertainty of SDMs and the importance of species distributions' drivers in space and time.Here we apply GSUA to MaxEnt that is one of the popular presence-only SDMs. We consider the Snowy Plover (Charadrius alexandrinus nivosus) (SP) in Florida that is a shorebird whose habitat is affected by sea level rise due to climate change. The importance of intrinsic and exogenous input factors to the uncertainty of the species distribution is evaluated for MaxEnt. GSUA is applied for three projections of the habitat (2006, 2060, and 2100) according to the A1B sea level rise scenario. The large land cover variation determines a moderate decrease in habitat suitability in 2060 and 2100 prospecting a low risk of decline for the SP. The regularization parameter for the environmental features, the uncertainty into the classification of salt-marsh, transitional marsh, and ocean beach, and the maximum number of iterations for the model training are in this order the most important input factors for the average habitat suitability. These results are related to the SP but, in general MaxEnt appears as a very non-linear model where uncertainty mostly derives from the interactions among input factors.The uncertainty of the output is a species-specific variable. Thus, GSUA need be performed for each case considering local exogenous input factors of the model. GSUA allows quantitative informed species-management decisions by providing scenarios with controlled uncertainty and confidence over factors' importance that can be used by resource managers.     

Developing an analytical model for planning systems verification,validation and testing processes

System VVT (verification, validation, and testing) are three tasks of System Engineering that focus on ensuring that systems are designed and delivered to meet customer and engineering requirements in the best way possible. Most organizations use sub-optimal VVT processes and methods. The literature does not offer an effective approach for associating VVT methods to VVT activities in order to satisfy customer and engineering requirements. In many large and complex projects, the project manager faces the dilemma of how best to validate and verify customer and engineering requirements, respectively. In many cases, decisions are made in an intuitive manner. For a project with a small amount of requirements (e.g., design of a new chair, table, or a simple toy), optimum decisions for VVT methods to be included within the project are feasible. For projects with large amount of requirements, for example, design of a new payload (e.g., captive carriage of a fuel tank, camera pod or other equipment) on an aircraft, a structured process to evaluate the overall impact of VVT methods implemented in order to satisfy those requirements, and the risk involved by performing these and not other methods, is necessary. This paper proposes a model for selecting an appropriate VVT approach depending on the phase or the level of the product in the system hierarchy; the model is independent of project size or precedence. We present an analytical model that not only structures the decision process but also outputs the optimal VVT methods given Cost and Risk constraints. The analytical model was formulated as an optimization problem, where a function that associates Quality derived from incorporating VVT methods is maximized subject to Cost and/or Risk constraints. The use of the model is demonstrated on a sample problem.     

Detection and discrimination of aquacultural facilities in Matsushima Bay,Japan, for integrated coastal zone management and marine spatial planning using full polarimetric L-band airborne synthetic aperture radar

Integrated coastal zone management (ICZM) and marine spatial planning (MSP) have been proposed for sustainable development of coastal zones. To implement ICZM and MSP, there is a need to establish database and informational networks to collect, share and disseminate information of the present situation of coastal zones. One permanent and concentrated use of coastal zones is hosting aquacultural facilities. This study aimed to develop a method to detect and discriminate aquacultural facilities in Matsushima Bay, Japan, using L-band polarimetric and interferometric airborne synthetic aperture radar (Pi-SAR-L2). Three-component-scattering model and eigenvalue–eigenvector decomposition were applied. The volume-scattering component images of the three-component-scattering model showed raft, longline, and rack aquacultural facilities from the sea surface in good contrast. The double-bounce-scattering component percentage discriminated rack aquacultural facilities from raft and longline aquacultural facilities. The size difference in the raft and longline aquacultural facilities was helpful for discriminating the type.     

Systematic modeling and model handling for manpower planning systems

The primary purpose of this paper is to show an efficient way of handling models and model data in a decision support system, in which it is usual to consider several variants of a model. The model data primarily consist of model-defining data, but the same approach may be used for the generated results as well. By efficient handling is meant the handling by the computer as well as by the user. For the user it is particularly important that new models can be conveniently defined as variants of existing models. The approach is introduced within the context of a decision support system for manpower planning based on Markov models. In the mean time the same approach has been used for the implementation of other decision support systems and has been found to be more generally applicable.     

Development of an integrated model for assessing the impact of diffuse and point source pollution on coastal waters

Pollution loads from land sources and their impact on the receiving waters can be predicted by using land-use and surface water quality models, respectively. In this paper details are given of the development of an integrated modelling system for managing water quality in coastal basins. The system includes a model linking the pollution input loads to land-use and a model for simulating surface flow and chemical and biological processes. The land-use model consists of two main components: a database and a model base. It uses a GIS system, namely ArcGIS, as the model platform. The database, built in the Geo-database format, includes six data sets containing information on social, economical, bathymetrical and hydrological aspects of a study area. The model base includes a series of transfer functions that link the pollution loads to key sources, including those from: industrial, domestic and agricultural inputs, and fish and animal farming. The water quality model is a numerical model which solves the governing equations representing the physical, chemical and biological processes in coastal waters. The modelling system was set up for Bohai Bay in China, with the land-use model being used to provide nutrient loadings from individual inputs and the water quality model used to predict the impact of these inputs on the receiving waters. Model simulations were also undertaken to predict the water quality conditions for various development and management scenarios.     

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.     

Network management of integrated banking systems

Network management has emerged as one of the most crucial issues for today's telecommunications planner. The integration of voice, data, text and image transmission and the application of digital technology present new problems and new opportunities. Organizational and technical solutions are necessary for large corporations and this is particularly true in banking. A further dimension of specific relevance to financial systems is the need for security.