A New CBR Approach to the Oil Spill Problem

Oil spills represent one of the most destructing environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be crucial in order to reduce the environmental risks. The system presented here forecasts the presence or not of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. The proposed system wraps other artificial intelligence techniques such as a Radial Basis Function Networks, Growing Cell Structures and Principal Components Analysis in order to develop the different phases of the CBR cycle. CBR systems have never been used before to solve oil slicks problems. The proposed system uses information obtained from various satellites such as salinity, temperature, pressure, number and area of the slicks... OSCBR system has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical data

Organization based multiagent architecture for distributed environments

[EN]Distributed environments represent a complex field in which applied solutions should be flexible and include significant adaptation capabilities. These environments are related to problems where multiple users and devices may interact, and where simple and local solutions could possibly generate good results, but may not be effective with regards to use and interaction. There are many techniques that can be employed to face this kind of problems, from CORBA to multi-agent systems, passing by web-services and SOA, among others. All those methodologies have their advantages and disadvantages that are properly analyzed in this documents, to finally explain the new architecture presented as a solution for distributed environment problems. The new architecture for solving complex solutions in distributed environments presented here is called OBaMADE: Organization Based Multiagent Architecture for Distributed Environments. It is a multiagent architecture based on the organizations of agents paradigm, where the agents in the architecture are structured into organizations to improve their organizational capabilities. The reasoning power of the architecture is based on the Case-Based Reasoning methology, being implemented in a internal organization that uses agents to create services to solve the external request made by the users. The OBaMADE architecture has been successfully applied to two different case studies where its prediction capabilities have been properly checked. Those case studies have showed optimistic results and, being complex systems, have demonstrated the abstraction and generalizations capabilities of the architecture. Nevertheless OBaMADE is intended to be able to solve much other kind of problems in distributed environments scenarios. It should be applied to other varieties of situations and to other knowledge fields to fully develop its potencial.[ES]Los entornos distribuidos representan un campo de conocimiento complejo en el que las soluciones a aplicar deben ser flexibles y deben contar con gran capacidad de adaptación. Este tipo de entornos está normalmente relacionado con problemas donde varios usuarios y dispositivos entran en juego. Para solucionar dichos problemas, pueden utilizarse sistemas locales que, aunque ofrezcan buenos resultados en términos de calidad de los mismos, no son tan efectivos en cuanto a la interacción y posibilidades de uso. Existen múltiples técnicas que pueden ser empleadas para resolver este tipo de problemas, desde CORBA a sistemas multiagente, pasando por servicios web y SOA, entre otros. Todas estas mitologías tienen sus ventajas e inconvenientes, que se analizan en este documento, para explicar, finalmente, la nueva arquitectura presentada como una solución para los problemas generados en entornos distribuidos. La nueva arquitectura aquí se llama OBaMADE, que es el acrónimo del inglés Organization Based Multiagent Architecture for Distributed Environments (Arquitectura Multiagente Basada en Organizaciones para Entornos Distribuidos). Se trata de una arquitectura multiagente basasa en el paradigma de las organizaciones de agente, donde los agentes que forman parte de la arquitectura se estructuran en organizaciones para mejorar sus capacidades organizativas. La capacidad de razonamiento de la arquitectura está basada en la metodología de razonamiento basado en casos, que se ha implementado en una de las organizaciones internas de la arquitectura por medio de agentes que crean servicios que responden a las solicitudes externas de los usuarios. La arquitectura OBaMADE se ha aplicado de forma exitosa a dos casos de estudio diferentes, en los que se han demostrado sus capacidades predictivas. Aplicando OBaMADE a estos casos de estudio se han obtenido resultados esperanzadores y, al ser sistemas complejos, se han demostrado las capacidades tanto de abstracción como de generalización de la arquitectura presentada. Sin embargo, esta arquitectura está diseñada para poder ser aplicada a más tipo de problemas de entornos distribuidos. Debe ser aplicada a más variadas situaciones y a otros campos de conocimiento para desarrollar completamente el potencial de esta arquitectura

Financial globalization and the Russian crisis of 1998

Russia had more-or-less completed the privatization of its manufacturing and natural resource sectors by the end of 1997. And in February 1998, the annual inflation rate at last dipped into the single digits. Privatization should have helped with stronger micro-foundations for growth. The conquest of inflation should have cemented macroeconomic credibility, lowered real interest rates, and spurred investment. Instead, Russia suffered a massivepublic debt-exchange rate-banking crisis just six months later, in August 1998. In showing how this turn of events unfolded, the authors focus on the interaction among Russia's deteriorating fiscal fundamentals, its weak micro-foundations of growth and financial globalization. They argue that the expectation of a large official bailout in the final 10 weeks before the meltdown played an important role, with Russia's external debt increasing by $16 billion or 8 percent of post-crisis gross domestic product during this time. The lessons and insights extracted from the 1998 Russian crisis are of general applicability, oil and geopolitics notwithstanding. These include a discussion of when financial globalization might actually hurt and a cutoff in market access might actually help; circumstances in which an official bailout could backfire; and why financial engineering tends to fail when fiscal solvency problems are present.Debt Markets,Emerging Markets,Banks&Banking Reform,Access to Finance,Currencies and Exchange Rates

Environmental Resource Management in Borderlands: Evolution from Competing Interests to Common Aversions

Great enthusiasm is attached to the emergence of cross-border regions (CBRs) as a new institutional arrangement for dealing with local cross-border environmental resource management and other issues that remain too distant from national capitals and/or too expensive to be addressed in the traditional topocraticmanner requiring instead local adhocratic methods. This study briefly discusses the perceived value of CBRs and necessary and sufficient conditions for the successful and sustainable development of such places. Then, assuming that necessary conditions can be met, the study investigates an intriguing hypothesis concerning the catalyzing of sustainable consensus for cross-border resource management based on a game theoretical approach that employs the use of dilemma of common aversion rather than the more traditional dilemma of competing common interests. Using this lens to investigate a series of events on the Pacific northwestern Canadian-American border in a part of the Fraser Lowland, we look for evidence of the emergence of an active and sustainable CBR to address local trans-border resource management issues. Although our micro-level scale fails to conclusively demonstrate such evidence, it does demonstrate the value of using this approach and suggests a number of avenues for further research

A forecasting solution to the oil spill problem based on a hybrid intelligent system

Oil spills represent one of the most destructive environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be critical in reducing environmental risks. The system presented here uses the Case-Based Reasoning (CBR) methodology to forecast the presence or absence of oil slicks in certain open sea areas after an oil spill. CBR is a computational methodology designed to generate solutions to certain problems by analysing previous solutions given to previously solved problems. The proposed CBR system includes a novel network for data classification and retrieval. This type of network, which is constructed by using an algorithm to summarize the results of an ensemble of Self-Organizing Maps, is explained and analysed in the present study. The Weighted Voting Superposition (WeVoS) algorithm mainly aims to achieve the best topographically ordered representation of a dataset in the map. This study shows how the proposed system, called WeVoS-CBR, uses information such as salinity, temperature, pressure, number and area of the slicks, obtained from various satellites to accurately predict the presence of oil slicks in the north-west of the Galician coast, using historical data

CROS: A Contingency Response multi-agent system for Oil Spills situations

This paper presents CROS, a Contingency Response multi-agent system for Oil Spill situations. The system uses the Case-Based Reasoning methodology to generate predictions to determine the probability of finding oil slicks in certain areas of the ocean. CBR uses past information to generate new solutions to the current problem. The system employs a SOA-based multi-agent architecture so that the main components of the system can be remotely accessed. Therefore, all functionalities (applications and services) can communicate in a distributed way, even from mobile devices. The core of the system is a group of deliberative agents acting as controllers and administrators for all applications and services. CROS manages information such as sea salinity, sea temperature, wind speed, ocean currents and atmosphere pressure, obtained from several sources, including satellite images. The system has been trained using historical data obtained after the Prestige accident on the Galician west coast of Spain. Results have demonstrated that the system can accurately predict the presence of oil slicks in determined zones after an oil spill. The use of a distributed multi-agent architecture has been shown to enhance the overall performance of the system

Forecasting the probability of finding oil slicks using a CBR system

A new predicting system is presented in which the aim is to forecast the presence of oil slicks in a certain area of the open sea after an oil spill. Case-based reasoning is a computational methodology designed to generate solutions to a certain problem by analysing previous solutions given to previous solved problems. In this case, the system designed to predict the presence of oil slicks wraps other artificial intelligence techniques such as a radial basis function networks, growing cell structures and principal components analysis in order to develop the different phases of the Case-based reasoning cycle. The proposed system uses information such as sea salinity, sea temperature, wind, currents, pressure, number and area of the slicks, …. obtained from various satellites. The system has been trained using data obtained after the Prestige oil spill, occurred in the Atlantic waters, in the northwest of Spain. The system developed has been able to accurately predict the presence of oil slicks in the north west of the Galician coast, using historical dat

Solving the Oil Spill Problem Using a Combination of CBR and a Summarization of SOM Ensembles

In this paper, a forecasting system is presented. It predicts the presence of oil slicks in a certain area of the open sea after an oil spill using Case-Based Reasoning methodology. CBR systems are designed to generate solutions to a certain problem by analysing historical data where previous solutions are stored. The system explained includes a novel network for data classification and retrieval. Such network works as a summarization algorithm for the results of an ensemble of Self-Organizing Maps. This algorithm, called Weighted Voting Superposition (WeVoS), is aimed to achieve the lowest topographic error in the map. The WeVoS-CBR system has been able to precisely predict the presence of oil slicks in the open sea areas of the north west of the Galician coast

Cement stabilisation of crude-oil-contaminated soil

© 2016, Thomas Telford Services Ltd. All rights reserved. Crude-oil-contaminated soils are usually considered unsuitable construction materials for earthworks. This paper presents an experimental investigation of the effects of applying Portland cement on the plasticity, strength and permeability of a crude-oil-contaminated soil in order to ascertain its suitability for use as an earthworks construction material. Series of specific gravity, Atterberg limits, compaction, strength and permeability characteristics were determined for a natural soil, the soil after being artificially contaminated with crude oil and the contaminated soil with varying proportions of added cement. It was found that the geotechnical properties of the soil became less desirable after contamination with crude oil, but the application of cement to the contaminated soil improved its properties by way of cation exchange, agglomeration and cementation. Cement stabilisation of crude-oil-contaminated soil provides a stable supporting structure, as well as a capping layer, that prevents the crude oil from interacting with the construction materials above. Thus, instead of disposing of contaminated soils, creating unnecessary waste and incurring costs, stabilisation with cement – which is practically feasible to undertake on site – makes such soils useful for supporting structural foundations or road pavement structures

Understanding Crude Oil Transport Strategies in North America

On July 6, 2013, an oil-laden unit train derailed and exploded in Lac-Mégantic, Quebec, killing 47 people, shocking many, and leading to significantly increased public scrutiny of crude oil by rail. Simultaneously, there has been intense scrutiny of several proposed pipelines from the oil sands of northern Alberta. Not only is there concern about the potential environmental impacts of the pipelines themselves, such as a potential spill of diluted bitumen (a form of crude oil to be shipped), but also about the consequences of greenhouse gas (GHG) emissions caused by the energy-intensiveness of bitumen production and refining. From the point of view of the railroads, until such impacts are considered through political and regulatory processes in Canada and the US, railroads deciding whether to invest in capacity to transport bitumen are presented with considerable uncertainty. Using both qualitative and quantitative approaches, this paper characterizes some of this uncertainty and discusses its short- and long-term implications for railroads and policy makers