A risk-based model for inspection and maintenance of cross-country petroleum pipeline

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Blur adaptation explained by a norm-based model of contrast adaptation

Adapting to blurred images makes in-focus images look too sharp, and vice-versa (Webster et al, 2002 Nature Neuroscience 5 839 - 840). We asked how such blur adaptation is related to contrast adaptation. Georgeson (1985 Spatial Vision 1 103 - 112) found that grating contrast adaptation followed a subtractive rule: perceived (matched) contrast of a grating was fairly well predicted by subtracting some fraction k(~0.3) of the adapting contrast from the test contrast. Here we apply that rule to the responses of a set of spatial filters at different scales and orientations. Blur is encoded by the pattern of filter response magnitudes over scale. We tested two versions - the 'norm model' and 'fatigue model' - against blur-matching data obtained after adaptation to sharpened, in-focus or blurred images. In the fatigue model, filter responses are simply reduced by exposure to the adapter. In the norm model, (a) the visual system is pre-adapted to a focused world and (b) discrepancy between observed and expected responses to the experimental adapter leads to additional reduction (or enhancement) of filter responses during experimental adaptation. The two models are closely related, but only the norm model gave a satisfactory account of results across the four experiments analysed, with one free parameter k. This model implies that the visual system is pre-adapted to focused images, that adapting to in-focus or blank images produces no change in adaptation, and that adapting to sharpened or blurred images changes the state of adaptation, leading to changes in perceived blur or sharpness.

A rule based model for the objective determination of the e-business requirements of a manufacturing organisation

The starting point of this research was the belief that manufacturing and similar industries need help with the concept of e-business, especially in assessing the relevance of possible e-business initiatives. The research hypotheses was that it should be possible to produce a systematic model that defines, at a useful level of detail, the probable e-business requirements of an organisation based on objective criteria with an accuracy of 85%-90%. This thesis describes the development and validation of such a model. A preliminary model was developed from a variety of sources, including a survey of current and planned e-business activity and representative examples of e-business material produced by e-business solution providers. The model was subject to a process of testing and refinement based on recursive case studies, with controls over the improving accuracy and stability of the model. Useful conclusions were also possible as to the relevance of e-business functions to the case study participants themselves. Techniques were evolved to synthesise the e-business requirements of an organisation and present them at a management summary level of detail. The results of applying these techniques to all the case studies used in this research were discussed. The conclusion of the research was that the case study methodology employed was successful. A model was achieved suitable for practical application in a manufacturing organisation requiring help with a requirements definition process.

The emergence of knowledge exchange:an agent-based model of a software market

We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

Risk-based model aids selection of pipeline inspection, maintenance strategies

The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.

NLSE-based model of a random distributed feedback fiber laser

In this work we propose a NLSE-based model of power and spectral properties of the random distributed feedback (DFB) fiber laser. The model is based on coupled set of non-linear Schrödinger equations for pump and Stokes waves with the distributed feedback due to Rayleigh scattering. The model considers random backscattering via its average strength, i.e. we assume that the feedback is incoherent. In addition, this allows us to speed up simulations sufficiently (up to several orders of magnitude). We found that the model of the incoherent feedback predicts the smooth and narrow (comparing with the gain spectral profile) generation spectrum in the random DFB fiber laser. The model allows one to optimize the random laser generation spectrum width varying the dispersion and nonlinearity values: we found, that the high dispersion and low nonlinearity results in narrower spectrum that could be interpreted as four-wave mixing between different spectral components in the quasi-mode-less spectrum of the random laser under study could play an important role in the spectrum formation. Note that the physical mechanism of the random DFB fiber laser formation and broadening is not identified yet. We investigate temporal and statistical properties of the random DFB fiber laser dynamics. Interestingly, we found that the intensity statistics is not Gaussian. The intensity auto-correlation function also reveals that correlations do exist. The possibility to optimize the system parameters to enhance the observed intrinsic spectral correlations to further potentially achieved pulsed (mode-locked) operation of the mode-less random distributed feedback fiber laser is discussed.

Ontology-Based Model of Representation of Knowledge about Language Mappings

The paper presents a short review of some systems for program transformations performed on the basis of the internal intermediate representations of these programs. Many systems try to support several languages of representation of the source texts of programs and solve the task of their translation into the internal representation. This task is still a challenge as it is effort-consuming. To reduce the effort, different systems of translator construction, ready compilers with ready grammars of outside designers are used. Though this approach saves the effort, it has its drawbacks and constraints. The paper presents the general idea of using the mapping approach to solve the task within the framework of program transformations and overcome the disadvantages of the existing systems. The paper demonstrates a fragment of the ontology model of high-level languages mappings onto the single representation and gives the example of how the description of (a fragment) a particular mapping is represented in accordance with the ontology model.

Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks

OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.

ICTM: an interval tessellation-based model for reliable topographic segmentation

This work introduces a tessellation-based model for the declivity analysis of geographic regions. The analysis of the relief declivity, which is embedded in the rules of the model, categorizes each tessellation cell, with respect to the whole considered region, according to the (positive, negative, null) sign of the declivity of the cell. Such information is represented in the states assumed by the cells of the model. The overall configuration of such cells allows the division of the region into subregions of cells belonging to a same category, that is, presenting the same declivity sign. In order to control the errors coming from the discretization of the region into tessellation cells, or resulting from numerical computations, interval techniques are used. The implementation of the model is naturally parallel since the analysis is performed on the basis of local rules. An immediate application is in geophysics, where an adequate subdivision of geographic areas into segments presenting similar topographic characteristics is often convenient.

A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks

OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.

A coupled movement and bioenergetics model to explore the spawning migration of anchovy in the Bay of Biscay

Adult anchovies in the Bay of Biscay perform north to south migration from late winter to early summer for spawning. However, what triggers and drives the geographic shift of the population remains unclear and poorly understood. An individual-based fish model has been implemented to explore the potential mechanisms that control anchovy's movement routes toward its spawning habitats. To achieve this goal, two fish movement behaviors – gradient detection through restricted area search and kinesis – simulated fish response to its dynamic environment. A bioenergetics model was used to represent individual growth and reproduction along the fish trajectory. The environmental forcing (food, temperature) of the model was provided by a coupled physical–biogeochemical model. We followed a hypothesis-testing strategy to actualize a series of simulations using different cues and computational assumptions. The gradient detection behavior was found as the most suitable mechanism to recreate the observed shift of anchovy distribution under the combined effect of sea-surface temperature and zooplankton. In addition, our results suggested that southward movement occurred more actively from early April to middle May following favorably the spatio-temporal evolution of zooplankton and temperature. In terms of fish bioenergetics, individuals who ended up in the southern part of the bay presented better condition based on energy content, proposing the resulting energy gain as an ecological explanation for this migration. The kinesis approach resulted in a moderate performance, producing distribution pattern with the highest spread. Finally, model performance was not significantly affected by changes on the starting date, initial fish distribution and number of particles used in the simulations, whereas it was drastically influenced by the adopted cues.

Fault tolerance logging-based model for deterministic systems

Fault tolerance allows a system to remain operational to some degree when some of its components fail. One of the most common fault tolerance mechanisms consists on logging the system state periodically, and recovering the system to a consistent state in the event of a failure. This paper describes a general fault tolerance logging-based mechanism, which can be layered over deterministic systems. Our proposal describes how a logging mechanism can recover the underlying system to a consistent state, even if an action or set of actions were interrupted mid-way, due to a server crash. We also propose different methods of storing the logging information, and describe how to deploy a fault tolerant master-slave cluster for information replication. We adapt our model to a previously proposed framework, which provided common relational features, like transactions with atomic, consistent, isolated and durable properties, to NoSQL database management systems.

Integration of a graph-based model indexer in commercial modelling tools

Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam’s clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam’s toolset. The first case study measured the performance of Hawk’s Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.

Testing a Theory-Based Model of Suicidality in a Community Sample

The aim of the present study is to test a theory-based model of suicide in a low-risk nonclinical sample. A community sample of convenience of 200 adults, 102 men and 98 women, responded to the Depressive Experiences Questionnaire, the Center for the Epidemiologic Studies of Depression Scale, the Psychache Scale, the Interpersonal Needs Questionnaire, and the Suicide Behaviors Questionnaire Revised. The hypothesized structural equation model, including trait dimensions of self-criticism and neediness, and state dimensions of depression, psychache, perceived burdensomeness, and thwarted belongingness, fit the observed data well and significantly explained 49% of the variance of suicidality.