Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically thecompliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

Decision Support Model for Assessing Archaeological Survey Needs for Bridge Replacement Projects in Iowa, 2006

The Bridges Decision Support Model is a geographic information system (GIS) that assembles existing data on archaeological sites, surveys, and their geologic contexts to assess the risk of bridge replacement projects encountering 13,000- to 150-year-old Native American sites. This project identifies critical variables for assessing prehistoric sites potential, examines the quality of available data about the variables, and applies the data to creating a decision support framework for use by the Iowa Department of Transportation (Iowa DOT) and others. An analysis of previous archaeological surveys indicates that subsurface testing to discover buried sites became increasingly common after 1980, but did not become routine until after the adoption of guidelines recommending such testing, in 1993. Even then, the average depth of testing has been relatively shallow. Alluvial deposits of sufficient age, deposited in depositional environments conducive to human habitation, are considerably thicker than archaeologists have routinely tested.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

”Tuntuu, et nää on vielä niin lapsen kengissä tämmöset HR:n luvut…”: Työhyvinvoinnin panostusten ja kustannusten Business Intelligence

Työhyvinvointi saa suomalaisessa työelämässä paljon huomiota juuri tällä hetkellä ja se on tunnis-tettu yrityksen kannalta hyödylliseksi alueeksi, johon kannattaa panostaa. Matalat työhyvinvointiin liittyvät kustannukset, organisaation parempi kilpailukyky ja maine sekä korkea henkilöstön tuotta-vuus ovat esimerkkejä työhyvinvoinnin kautta saavutettavista hyödyistä. Yritys voi parantaa hen-kilöstön työhyvinvointia panostamalla siihen ja tämän pitäisi näkyä suoraan myös työhyvinvointiin liittyvissä tunnusluvuissa, kuten sairauspoissaolo-, työkyvyttömyyseläke- ja vaihtuvuuskustannuk-sissa. Yritykset voivat hyödyntää työhyvinvoinnin panostusten ja kustannusten tunnuslukuja, jos niitä hallitaan onnistuneesti. Tällöin pitää tietää, mistä kustannukset koostuvat ja ymmärtää, millä pa-nostuksilla niihin voidaan vaikuttaa. Business Intelligence on termi, jolla tarkoitetaan kaikkea sel-laista organisaation tiedon hallintaa, jota tarvitaan liiketoiminnan johtamisessa. Sen tavoitteena on tukea organisaatiossa tapahtuvaa päätöksentekoa. Business Intelligence voidaan kuvata prosessina, jossa organisaatio kerää, yhdistelee ja analysoi tietoa eri tietolähteistä. Analysoinnin jälkeen yrityk-sellä on käytössään uutta tietämystä, jota voidaan hyödyntää päätöksenteossa. Toimivien Business Intelligence ratkaisujen ansiosta yrityksen päätöksenteon varmuus ja vaikuttavuus kasvaa. Tämän tutkimuksen tarkoituksena on selvittää, millainen on tehokas työhyvinvoinnin panostusten ja kustannusten hallintaan liittyvä Business Intelligence prosessi. Tehokas prosessi auttaa paranta-maan työhyvinvointiin tehtävien panostusten oikeellisuutta ja nostaa organisaation ymmärrystä omasta toiminnastaan. Tutkimusongelmaan on haettu vastauksia laadullisten tutkimusmenetelmien avulla haastattelemalla työhyvinvoinnin panostusten ja kustannusten tunnuslukuja seuraavia yrityk-siä. Tutkimuksen tulokset on analysoitu käyttämällä hyväksi kirjallisuuteen perustuvaa teema-ana-lyysia, jossa työhyvinvointiin ja Business Intelligenceen liittyvää teoriaa verrataan haastatteluista saatuihin vastauksiin. Tutkimuksen johtopäätöksenä tehokas työhyvinvoinnin panostusten ja kustannusten Business Intelligence prosessi voidaan kuvata perinteisten BI:n tasojen kautta. Työhyvinvoinnin panostusten ja kustannusten tunnuslukujen kerääminen onnistuu eri osapuolten välisen yhteistyön avulla. Tun-nusluvuista voi luoda merkityksellistä tietämystä, kun niistä saa tarkkaa tietoa ja niiden rinnalle tuodaan laadullista aineistoa työntekijöiden kokemuksista. Prosessia tukee se, jos teknologian kautta päätöksentekijä pystyy hankkimaan tarvittavat tiedot itse. Tulevaisuudessa olisi tärkeää, että saa-daan enemmän tietoa eri toimenpiteiden vaikuttavuudesta tunnuslukuihin, jotta päätöksiä voidaan tehdä luotettavamman tietämyksen varassa.

Liiketoimintatiedonhallinnan hyödyntämisen esteet päätettäessä palveluista. Case: Kunnalliset pelastustoimen liikelaitokset ja eriytetyt taseyksiköt

Pelastuslaitosten liiketoimintatiedonhallinnalla, tietoperusteisuudella ja tietojohtamisella on tulevaisuudessa merkittävä rooli päätettäessä palveluista. Julkisen pelastustoimen kuntien liikelaitoksina ja eriytettyinä taseyksiköinä toimivien pelastuslaitosten haasteet tulevat olemaan jatkossa tehokkaiden ja vaikuttavien palveluiden strategisessa johtamisessa ja suunnittelussa. Näistä asioista päättäminen on kriittinen vaihe onnistumisen kannalta. Päätöksenteko eri tasoilla tarvitsee tuekseen toiminnasta ja palveluista kanavoitua analysoitua tietoa. Asiakastarpeesta lähtevä vaikuttavuus ja laatu korostuvat. Liiketoimintatiedonhallinta ja tietoperusteisuus haastavat pelastuslaitoksen johtamisjärjestelmän. Johtamisen kyvykkyys ja henkilöstön osaaminen ovat tietoperusteisuuden ja tiedonhallinnan keskiössä. Systemaattisen liiketoimintatiedonhallinnan ja tietoperusteisuuden erottaa perinteisestä virkamiehen tietojen hyväksikäytöstä käsitteen kokonaisvaltaisuus ja järjestelmällisyys kaikessa tiedollisessa toiminnassa. Tämä kattaa tietojärjestelmät, mittarit, prosessit, strategian suunnitelmat, asiakirjat, raportoinnin, kehittämisen ja tutkimuksen. Liiketoimin-tatiedonhallinta ja tietojohtaminen linkittävät kaiken toisiinsa muodostaen keskinäisriippuvaisen yhtenäisen järjestelmän ja kokonaisvaltaisen ymmärryksen. Tutkimukseni on laadullinen tutkimus jossa tiedon keruu ja analysointi on toteutettu toisiaan tukevilla tutkimusotteilla. Metodologia nojaa teorialähtöiseen systemaattiseen analyysiin, jossa on valikoituja osia sisällön analyysistä. Tutkimuksessa on käytetty aineisto- ja menetelmätriangulaatioita. Tutkimuksen aineisto on kerätty teemahaastatteluilla valittujen kohde pelastuslaitosten asiantuntijoilta palveluiden päätös- ja suunnittelutasolta, johtoryhmistä ja joh-tokunnista. Haastatteluja varten tutkija on tutustunut kohdepelastuslaitosten palveluita mää-rittävään tiedolliseen dokumentaatioon kuten palvelutasopäätöksiin ja riskianalyyseihin. Ai-neisto keruun kohteiksi valikoitui pääkaupunkiseudun alueen pelastuslaitokset: Helsingin kaupungin pelastuslaitos sekä Itä-, Keski- ja Länsi-Uudenmaan pelastuslaitokset. Tulosten mukaan pelastuslaitosten keskeiset liiketoimintatiedonhallinnan esteet muodostuvat johtamisen ongelmista, organisaation muutosvastarinnasta ja päätöksenteon tietoperusteen puutteesta. Nämä ilmenevät strategisen johtamisen puutteina, vaikuttavuuden mittaamisen sekä tiedon jalostamisen ongelmina. Keskeistä tiedollista yhdistävää ja linkittävää tekijää ei tunnisteta ja löydetä. Tiedollisessa liiketoimintatiedonhallinnan prosessityössä voisi olla tulos-ten mukaan mahdollisuuksia tämän tyhjiön täyttämiseen. Pelastuslaitoksille jää tulevaisuudessa valinta suunnasta johon ne haluavat edetä tiedonhal-linnan, tietojohtamisen ja tietoperusteisuuden kanssa. Tämä vaikuttaa kehitykseen ja tavoitteeseen keskeisistä palveluiden päätöksentekoa tukevista johtamis- ja tietojärjestelmistä, tietoa kokoavista ja luovista dokumenteista sekä organisaation joustavasta rakenteesta. Tietoprosessiin, tiedon prosessimaiseen johtamiseen ja systemaattiseen tiedonhallintaan meneminen vaikuttaa tutkimuksen tulosten mukaan lupaavalta mahdollisuudelta. Samalla se haastaa pelauslaitokset suureen kulttuuriseen muutokseen ja asettaa uusien vaikuttavuusmittareiden tuottaman tiedon ennakoivan hyväksynnän vaateen strategiselle suunnittelulle. Tämä vaatii pelastuslaitosten johdolta ja henkilöstöltä osaamista, yhteisymmärrystä, muutostarpeiden hyväksyntää sekä asiakkaan asettamista vaikuttavuuden keskiöön.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

A formalization for multi-agent decision support in cooperative environments. A framework for situated agents

La tesis propone un marco de trabajo para el soporte de la toma de decisiones adecuado para soportar la ejecución distribuida de acciones cooperativas en entornos multi-agente dinámicos y complejos. Soporte para la toma de decisiones es un proceso que intenta mejorar la ejecución de la toma de decisiones en escenarios cooperativos. Este proceso ocurre continuamente en la vida diaria. Los humanos, por ejemplo, deben tomar decisiones acerca de que ropa usar, que comida comer, etc. En este sentido, un agente es definido como cualquier cosa que está situada en un entorno y que actúa, basado en su observación, su interpretación y su conocimiento acerca de su situación en tal entorno para lograr una acción en particular.Por lo tanto, para tomar decisiones, los agentes deben considerar el conocimiento que les permita ser consientes en que acciones pueden o no ejecutar. Aquí, tal proceso toma en cuenta tres parámetros de información con la intención de personificar a un agente en un entorno típicamente físico. Así, el mencionado conjunto de información es conocido como ejes de decisión, los cuales deben ser tomados por los agentes para decidir si pueden ejecutar correctamente una tarea propuesta por otro agente o humano. Los agentes, por lo tanto, pueden hacer mejores decisiones considerando y representando apropiadamente tal información. Los ejes de decisión, principalmente basados en: las condiciones ambientales, el conocimiento físico y el valor de confianza del agente, provee a los sistemas multi-agente un confiable razonamiento para alcanzar un factible y exitoso rendimiento cooperativo.Actualmente, muchos investigadores tienden a generar nuevos avances en la tecnología agente para incrementar la inteligencia, autonomía, comunicación y auto-adaptación en escenarios agentes típicamente abierto y distribuidos. En este sentido, esta investigación intenta contribuir en el desarrollo de un nuevo método que impacte tanto en las decisiones individuales como colectivas de los sistemas multi-agente. Por lo tanto, el marco de trabajo propuesto ha sido utilizado para implementar las acciones concretas involucradas en el campo de pruebas del fútbol robótico. Este campo emula los juegos de fútbol real, donde los agentes deben coordinarse, interactuar y cooperar entre ellos para solucionar tareas complejas dentro de un escenario dinámicamente cambiante y competitivo, tanto para manejar el diseño de los requerimientos involucrados en las tareas como para demostrar su efectividad en trabajos colectivos. Es así que los resultados obtenidos tanto en el simulador como en el campo real de experimentación, muestran que el marco de trabajo para el soporte de decisiones propuesto para agentes situados es capaz de mejorar la interacción y la comunicación, reflejando en un adecuad y confiable trabajo en equipo dentro de entornos impredecibles, dinámicos y competitivos. Además, los experimentos y resultados también muestran que la información seleccionada para generar los ejes de decisión para situar a los agentes, es útil cuando tales agentes deben ejecutar una acción o hacer un compromiso en cada momento con la intención de cumplir exitosamente un objetivo colectivo. Finalmente, algunas conclusiones enfatizando las ventajas y utilidades del trabajo propuesto en la mejora del rendimiento colectivo de los sistemas multi-agente en situaciones tales como tareas coordinadas y asignación de tareas son presentadas.

Development, implementation and evaluation of an activated sludge supervisory system for the Granollers WWTP

La present tesi pretén recollir l'experiència viscuda en desenvolupar un sistema supervisor intel·ligent per a la millora de la gestió de plantes depuradores d'aigües residuals., implementar-lo en planta real (EDAR Granollers) i avaluar-ne el funcionament dia a dia amb situacions típiques de la planta. Aquest sistema supervisor combina i integra eines de control clàssic de les plantes depuradores (controlador automàtic del nivell d'oxigen dissolt al reactor biològic, ús de models descriptius del procés...) amb l'aplicació d'eines del camp de la intel·ligència artificial (sistemes basats en el coneixement, concretament sistemes experts i sistemes basats en casos, i xarxes neuronals). Aquest document s'estructura en 9 capítols diferents. Hi ha una primera part introductòria on es fa una revisió de l'estat actual del control de les EDARs i s'explica el perquè de la complexitat de la gestió d'aquests processos (capítol 1). Aquest capítol introductori juntament amb el capítol 2, on es pretén explicar els antecedents d'aquesta tesi, serveixen per establir els objectius d'aquest treball (capítol 3). A continuació, el capítol 4 descriu les peculiaritats i especificitats de la planta que s'ha escollit per implementar el sistema supervisor. Els capítols 5 i 6 del present document exposen el treball fet per a desenvolupar el sistema basat en regles o sistema expert (capítol 6) i el sistema basat en casos (capítol 7). El capítol 8 descriu la integració d'aquestes dues eines de raonament en una arquitectura multi nivell distribuïda. Finalment, hi ha una darrer capítol que correspon a la avaluació (verificació i validació), en primer lloc, de cadascuna de les eines per separat i, posteriorment, del sistema global en front de situacions reals que es donin a la depuradora

Multi-agent collaboration for decision support in shared zones of intelligent buildings

In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented.

Utilização de business intelligence para gestão de área operacional de agências bancárias : um estudo de caso

A eficiência operacional nos bancos é um fator que vem ganhando importância em função da evolução no cenário econômico, apontando para maior competitividade. Nesse contexto, a gestão operacional agências torna-se cada vez mais relevante. Entretanto, a atividade de gerenciar milhares de agências, com necessidade de agilidade na tomada de decisões, mostra-se complexa. Nesse sentido, o Business Intelligence se apresenta como uma solução para otimizar a atividade de gestão, adicionando inteligência ao negócio. Não obstante, questões práticas de implementação e uso são desafios para unir BI e gestão de agências bancárias. Este trabalho analisa a aplicação de Business Intelligence para a gestão operacional de agências bancárias em busca de práticas relevantes. O método de pesquisa utilizado é o estudo de caso, aplicado em uma grande instituição financeira nacional. Por meio de consulta a documentações, entrevistas com Gerentes Regionais e Equipe de Projeto buscou-se verificar proposições que foram depreendidas da revisão da literatura sob dois aspectos: implementação e utilização da solução de BI. Como resultado, foram confirmadas as proposições apontando para importância do apoio da organização e alinhamento ao negócio para uma implementação bem sucedida, além da constatação que BI não pode ser tratado apenas como uma ferramenta, na verdade além da parte técnica, envolve processos e negócios. Com relação à utilização, foi verificado que BI traz mais qualidade à informação, melhora o suporte ao processo de tomada de decisão e trás benefícios intangíveis e tangíveis para a gestão operacional de agências bancárias, como aumento da produtividade, redução de custos e riscos e melhor atendimento ao cliente.

A relação entre business intelligence e o processo de inovação no mercado de cartões de crédito brasileiro : um estudo de caso

As ferramentas de Business Intelligence se tornaram elemento importante no contexto organizacional em função de fornecerem às empresas informações necessárias para o processo decisório. Para garantir vantagem competitiva perante os concorrentes, as empresas buscam inovar. O processo atrelado ao fenômeno da inovação é complexo e depende de uma série de fatores, tais como regulação, pressão do consumidor e tecnologia. O mercado de cartões de crédito no Brasil cresce em ritmo acelerado, com recente concentração em poucos competidores e grande variedade de produtos ofertados. Assim dito, a presente pesquisa busca analisar de que maneira o ferramental de BI se relaciona com o processo de inovação no setor de cartões de crédito brasileiro. O método de pesquisa escolhido foi o estudo de caso, realizado em uma empresa emissora de cartões de crédito com tradição no mercado. A partir de entrevistas semi-estruturadas com executivos de diversas áreas, de coleta de documentação existente e estudo das ferramentas de BI aplicadas no caso, propõe-se uma matriz da relação entre as ferramentas de BI e inovação. Como resultado conclui-se que as ferramentas de BI podem influenciar diretamente o processo de inovação, definindo novos atributos de preço, segmentos e programas de incentivo, ou indiretamente, servindo somente como insumo para discussões, identificação de gaps e formulação de estratégias, tendo uma relação indireta com o processo de inovação.

Desenvolvimento de um sistema computacional para geração automática de mapas de vulnerabilidade como ferramenta de auxílio às ações de prevenção ao derramamento de óleo em áreas costeiras

The northern portion of the Rio Grande do Norte State is characterized by intense coastal dynamics affecting areas with ecosystems of moderate to high environmental sensitivity. In this region are installed the main socioeconomic activities of RN State: salt industry, shrimp farm, fruit industry and oil industry. The oil industry suffers the effects of coastal dynamic action promoting problems such as erosion and exposure of wells and pipelines along the shore. Thus came the improvement of such modifications, in search of understanding of the changes which causes environmental impacts with the purpose of detecting and assessing areas with greater vulnerability to variations. Coastal areas under influence oil industry are highly vulnerable and sensitive in case of accidents involving oil spill in the vicinity. Therefore, it was established the geoenvironmental monitoring of the region with the aim of evaluating the entire coastal area evolution and check the sensitivity of the site on the presence of oil. The goal of this work was the implementation of a computer system that combines the needs of insertion and visualization of thematic maps for the generation of Environmental Vulnerability maps, using techniques of Business Intelligence (BI), from vector information previously stored in the database. The fundamental design interest was to implement a more scalable system that meets the diverse fields of study and make the appropriate system for generating online vulnerability maps, automating the methodology so as to facilitate data manipulation and fast results in cases of real time operational decision-making. In database development a geographic area was established the conceptual model of the selected data and Web system was done using the template database PostgreSQL, PostGis spatial extension, Glassfish Web server and the viewer maps Web environment, the GeoServer. To develop a geographic database it was necessary to generate the conceptual model of the selected data and the Web system development was done using the PostgreSQL database system, its spatial extension PostGIS, the web server Glassfish and GeoServer to display maps in Web

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.