Predicting and diagnosing faults in wastewater treatment process by Bayesian Belief Networks

Diagnosing faults in wastewater treatment, like diagnosis of most problems, requires bi-directional plausible reasoning. This means that both predictive (from causes to symptoms) and diagnostic (from symptoms to causes) inferences have to be made, depending on the evidence available, in reasoning for the final diagnosis. The use of computer technology for the purpose of diagnosing faults in the wastewater process has been explored, and a rule-based expert system was initiated. It was found that such an approach has serious limitations in its ability to reason bi-directionally, which makes it unsuitable for diagnosing tasks under the conditions of uncertainty. The probabilistic approach known as Bayesian Belief Networks (BBNS) was then critically reviewed, and was found to be well-suited for diagnosis under uncertainty. The theory and application of BBNs are outlined. A full-scale BBN for the diagnosis of faults in a wastewater treatment plant based on the activated sludge system has been developed in this research. Results from the BBN show good agreement with the predictions of wastewater experts. It can be concluded that the BBNs are far superior to rule-based systems based on certainty factors in their ability to diagnose faults and predict systems in complex operating systems having inherently uncertain behaviour.

A probabilistic model for trust and reputation

This paper concerns the problem of agent trust in an electronic market place. We maintain that agent trust involves making decisions under uncertainty and therefore the phenomenon should be modelled probabilistically. We therefore propose a probabilistic framework that models agent interactions as a Hidden Markov Model (HMM). The observations of the HMM are the interaction outcomes and the hidden state is the underlying probability of a good outcome. The task of deciding whether to interact with another agent reduces to probabilistic inference of the current state of that agent given all previous interaction outcomes. The model is extended to include a probabilistic reputation system which involves agents gathering opinions about other agents and fusing them with their own beliefs. Our system is fully probabilistic and hence delivers the following improvements with respect to previous work: (a) the model assumptions are faithfully translated into algorithms; our system is optimal under those assumptions, (b) It can account for agents whose behaviour is not static with time (c) it can estimate the rate with which an agent's behaviour changes. The system is shown to significantly outperform previous state-of-the-art methods in several numerical experiments. Copyright © 2010, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Fuzzy data envelopment analysis:a discrete approach

Data envelopment analysis (DEA) as introduced by Charnes, Cooper, and Rhodes (1978) is a linear programming technique that has widely been used to evaluate the relative efficiency of a set of homogenous decision making units (DMUs). In many real applications, the input-output variables cannot be precisely measured. This is particularly important in assessing efficiency of DMUs using DEA, since the efficiency score of inefficient DMUs are very sensitive to possible data errors. Hence, several approaches have been proposed to deal with imprecise data. Perhaps the most popular fuzzy DEA model is based on a-cut. One drawback of the a-cut approach is that it cannot include all information about uncertainty. This paper aims to introduce an alternative linear programming model that can include some uncertainty information from the intervals within the a-cut approach. We introduce the concept of "local a-level" to develop a multi-objective linear programming to measure the efficiency of DMUs under uncertainty. An example is given to illustrate the use of this method.

Proactive environmental systems:the next generation of environmental monitoring

In this article we envision factors and trends that shape the next generation of environmental monitoring systems. One key factor in this respect is the combined effect of end-user needs and the general development of IT services and their availability. Currently, an environmental (monitoring) system is assumed to be reactive. It delivers measurement data and computational results only if the user explicitly asks for it either by query or subscription. There is a temptation to automate this by simply pushing data to end-users. This, however, leads easily to an "advertisement strategy", where data is pushed to end-users regardless of users' needs. Under this strategy, the mere amount of received data obfuscates the individual messages; any "automatic" service, regardless of its fitness, overruns a system that requires the user's initiative. The foreseeable problem is that, unless there is no overall management, each new environmental service is going to compete for end-users' attention and, thus, inadvertently hinder the use of existing services. As the main contribution we investigate the nature of proactive environmental systems, and how they should be designed to avoid the aforementioned problem. We also discuss how semantics, participatory sensing, uncertainty management, and situational awareness link to proactive environmental systems. We illustrate our proposals with some real-life examples.

Fuzzy assessment of performance of a decision making units using DEA:a non-radical approach

Data Envelopment Analysis (DEA) is recognized as a modern approach to the assessment of performance of a set of homogeneous Decision Making Units (DMUs) that use similar sources to produce similar outputs. While DEA commonly is used with precise data, recently several approaches are introduced for evaluating DMUs with uncertain data. In the existing approaches many information on uncertainties are lost. For example in the defuzzification, the a-level and fuzzy ranking approaches are not considered. In the tolerance approach the inequality or equality signs are fuzzified but the fuzzy coefficients (inputs and outputs) are not treated directly. The purpose of this paper is to develop a new model to evaluate DMUs under uncertainty using Fuzzy DEA and to include a-level to the model under fuzzy environment. An example is given to illustrate this method in details.

Financial Decisions via Methods of Guaranteed Control Theory

AMS subject classification: 93C95, 90A09.

A Collaborative Multiagent Framework based on Online Risk-Aware Planning and Decision-Making

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions. 

The Meanings of New Money: Social Constructions of Value in the Rise of Digital Currencies

Thesis (Ph.D.)--University of Washington, 2016-07

Constraints to the efficacy of risk management process in entrepreneurial companies

This paper highlights potential factors that affect the degree of efficacy of a formal risk management framework in entrepreneurial organisations. The understanding of entrepreneur’s self-schemas, entrepreneurial organisational culture and working environment is crucial to evaluate the efficacy of a risk management process. This research pointed out two main issues: i) the entrepreneurial decision making process with presence of biases and heuristics in judgement under uncertainty; and ii) the entrepreneurial organisational context that might create constraints to the implementation of a risk management framework.

Maxmin with multiple tastes and beliefs

Tese (doutorado)—Universidade de Brasília, Departamento de Economia, Brasília, 2016.

Factores económicos do risco sistemático nas carteiras de investimento: o caso português

Dissertação de mest. em Ciências Económicas e Empresariais, Unidade de Ciências Económicas e Empresariais, Univ. do Algarve, 1996

La disrupción: el punto de partida de la resiliencia o del fracaso empresarial (reflexiones desde la ingeniería)

La perdurabilidad empresarial ha sido un tema recurrente en la literatura sobre dirección de empresas. A pesar de los avances, la liquidación de las empresas aumenta permanentemente. Buscando alternativas de mejora se estudia el caso de dos empresas cuadragenarias dedicadas a prestar servicios de consultoría en ingeniería eléctrica y civil que, en condiciones de crisis, implementaron acciones que les permitieron, no sólo mantenerse en el mercado sino también fortalecer su estructura financiera. Los resultados demostraron que un enfoque equilibrado caracterizado por la toma oportuna de decisiones y la definición e implementación de estrategias de negocio efectivas constituyen herramientas óptimas para asegurar un mayor grado de resiliencia empresarial.

El exceso de confianza y el statu quo dentro de la estructuración de capital: una perspectiva de las finanzas corporativas del comportamiento

El presente artículo, presenta un análisis de las decisiones de estructuración de capital de la compañía Merck Sharp & Dome S.A.S, desde la perspectiva de las finanzas comportamentales, comparando los métodos utilizados actualmente por la compañía seleccionada con la teoría tradicional de las finanzas, para así poder evaluar el desempeño teórico y real. Incorporar elementos comportamentales dentro del estudio permite profundizar más sobre de las decisiones corporativas en un contexto más cercano a los avances investigativos de las finanzas del comportamiento, lo cual lleva a que el análisis de este artículo se enfoque en la identificación y entendimiento de los sesgos de exceso de confianza y statu quo, pero sobre todo su implicación en las decisiones de financiación. Según la teoría tradicional el proceso de estructuración de capital se guía por los costos, pero este estudio de caso permitió observar que en la práctica esta relación de costo-decisión está en un segundo lugar, después de la relación riesgo-decisión a la hora del proceso de estructuración de capital.

la influencia de la felicidad en las decisiones de inversión de activos de largo plazo para una muestra de siete gerentes financieros en la ciudad de Bogotá en el año 2016.

El presente artículo contribuye con la investigación de las Finanzas Corporativas del Comportamiento, rama de las finanzas corporativas que considera que el individuo que toma decisiones financieras no es completamente racional y que por hecho existen sesgos psicológicos que influyen en sus decisiones. Este documento se enfoca, desde el punto de vista conceptual y también mediante el análisis de un estudio de campo, en la influencia de la felicidad en las decisiones de inversión en activos de largo plazo para un grupo de siete gerentes ubicados en la ciudad de Bogotá en el año 2016. En el documento se abarca el concepto general de las finanzas corporativas del comportamiento, se define la felicidad y se presentan sub-variables determinantes para la felicidad del individuo como lo son: salud, balance vida/trabajo, educación y habilidades, conexiones sociales y medio ambiente. Finalmente se presenta cómo éstas afectan a los gerentes financieros en sus decisiones de acuerdo a la investigación realizada.

Essays on Information Economics

This thesis consists of three essays on information economics. I explore how information is strategically communicated or designed by senders who aim to influence the decisions of a receiver. In the first chapter, I study a cheap talk game between two imperfectly informed experts and a decision maker. The experts receive noisy signals about the state and sequentially communicate the relevant information to the decision maker. I refine the self-serving belief system under uncertainty and Ι characterise the most informative equilibrium that might arise in such environments.In the second chapter, I consider the case where a decision maker seeks advice from a biased expert who cares also about establishing a reputation of being competent. The expert has the incentives to misreport her information but she faces a trade-off between the gain from misrepresentation and the potential reputation loss. I show that the equilibrium is fully-revealing if the expert is not too biased and not too highly reputable. If there is competition between two experts the information transmission is always improved. However, in cases where the experts are more than two the result is ambiguous, and it depends on the players’ prior belief over states.In the last chapter, I consider a model of strategic communication where a privately and imperfectly informed sender can persuade a receiver. The sender may receive favorable or unfavorable private information about her preferred state. I describe two ways that are adopted in real life situations and theoretically improve equilibrium informativeness given sender's private information. First, a policy that suggests symmetry constraints to the experiments' choice. Second, an approval strategy characterised by a low precision threshold where the receiver will accept the sender with a positive probability and a higher one where the sender will be accepted with certainty.