Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Thermal modelling for dynamic transformer rating in low carbon distribution network operation

Dynamic asset rating is one of a number of techniques that could be used to facilitate low carbon electricity network operation. This paper focusses on distribution level transformer dynamic rating under this context. The models available for use with dynamic asset rating are discussed and compared using measured load and weather conditions from a trial Network area within Milton Keynes. The paper then uses the most appropriate model to investigate, through simulation, the potential gains in dynamic rating compared to static rating under two transformer cooling methods to understand the potential gain to the Network Operator.

Distribution modeling of nonlinear inverse controllers under a Bayesian framework

The inverse controller is traditionally assumed to be a deterministic function. This paper presents a pedagogical methodology for estimating the stochastic model of the inverse controller. The proposed method is based on Bayes' theorem. Using Bayes' rule to obtain the stochastic model of the inverse controller allows the use of knowledge of uncertainty from both the inverse and the forward model in estimating the optimal control signal. The paper presents the methodology for general nonlinear systems and is demonstrated on nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) examples. © 2006 IEEE.

The effect of climate change on the potential distribution of the European Phlebotomus species and the parasite Leishmania infantum in 2011-2070. A climate envelope modeling approach

Aims: In the Mediterranean areas of Europe, leishmanisasis is one of the most emerging vector-borne diseases. Members of genus Phlebotomus are the primary vectors of the genus Leishmania. To track the human health effect of climate change it is a very important interdisciplinary question to study whether the climatic requirements and geographical distribution of the vectors of human pathogen organisms correlate with each other. Our study intended to explore the potential effects of ongoing climate change, in particular through a potential upward altitudinal and latitudinal shift of the distribution of the parasite Leishmania infantum, its vectors Phlebotomus ariasi, P. neglectus, P. perfiliewi, P. perniciosus, and P. tobbi, and some other sandfly species: P. papatasi, P. sergenti, and P. similis. Methods: By using a climate envelope modelling (CEM) method we modelled the current and future (2011-2070) potential distribution of 8 European sandfly species and L. infantum based on the current distribution using the REMO regional climate model. Results: We found that by the end of the 2060’s most parts of Western Europe can be colonized by sandfly species, mostly by P. ariasi and P. pernicosus. P. ariasi showed the greatest potential northward expansion. For all the studied vectors of L. infantum the entire Mediterranean Basin and South-Eastern Europe seemed to be suitable. L. infantum can affect the Eastern Mediterranean, without notable northward expansion. Our model resulted 1 to 2 months prolongation of the potentially active period of P. neglectus P. papatasi and P. perniciosus for the 2060’s in Southern Hungary. Conclusion: Our findings confirm the concerns that leishmanisais can become a real hazard for the major part of the European population to the end of the 21th century and the Carpathian Basin is a particularly vulnerable area.

Modeling the future distribution of Mediterranean Pinus species

The potential future distribution of four Mediterranean pines was aimed to be modeled supported by EUFORGEN digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method), and REMO regional climate model (climatic data). The studied species were Pinus brutia, Pinus halepensis, Pinus pinaster, and Pinus pinea. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The climate model was based on the IPCC SRES A1B scenario. The model results show explicit shift of the distributions to the north in case of three of the four studied species. The future (2041-70) climate of Western Hungary seems to be suitable for Pinus pinaster.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Projecting Changes in the Distribution and Productivity of Living Marine Resources: A Critical Review of the Suite of Modeling Approaches used in the Large European Project VECTORS

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

Modeling the distribution of crossovers and interference with mice DNA data

Chiasma and crossover are two related biological processes of great importance in the understanding genetic variation. The study of these processes is straightforward in organisms where all products of meiosis are recovered and can be observed. This is not the case in mammals. Our understanding of these processes depends on our ability to model them. In this study I describe the biological processes that underline chiasma and crossover as well as the two main inference problems associated with these processes: i) in mammals we only recover one of the four products of meiosis and, ii) in general, we do not observe where the crossovers actually happen, but we find an interval containing type-2 censored information. NPML estimate was proposed and used in this work and used to compare chromosome length and chromosome expansion through the crosses.

Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula

We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10 10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model’s spatial resolution by extrapolating it to 1 1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. # 2003 Elsevier Ltd. All rights reserved.

Modeling study on transport organization methods choice of highway rapid passenger transport in China

Some new types of mathematical model among four key techno - economic indexes of highway rapid passenger through transportation were established based on the principles of transportation economics. According to the research on the feasible solutions to the associated parameters which were then compared to the actual value, found some limitation in the existing transport organization method. In order to conquer that, two new types of transport organization method, namely CD (Collecting and Distributing) Method and Relay Method were brought forward. What’s more, a further research was down to estimate their characteristics, such as feasibilities, operation flows, applicability fields, etc. This analysis proves the two methods can offset the shortage of rapid passenger through transportation. To ensure highway rapid passenger transport develop harmoniously, a three-stage development targets was suggested to fuse different organization methods.

Application of micro CT and computation modeling in bone tissue engineering

Computer aided technologies, medical imaging, and rapid prototyping has created new possibilities in biomedical engineering. The systematic variation of scaffold architecture as well as the mineralization inside a scaffold/bone construct can be studied using computer imaging technology and CAD/CAM and micro computed tomography (CT). In this paper, the potential of combining these technologies has been exploited in the study of scaffolds and osteochondral repair. Porosity, surface area per unit volume and the degree of interconnectivity were evaluated through imaging and computer aided manipulation of the scaffold scan data. For the osteochondral model, the spatial distribution and the degree of bone regeneration were evaluated. In this study the versatility of two softwares Mimics (Materialize), CTan and 3D realistic visualization (Skyscan) were assessed, too.

Optimal voltage support mechanism in distribution networks

Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.