Developing a labelled object-relational constraint database architecture for the projection operator

Current relational databases have been developed in order to improve the handling of stored data, however, there are some types of information that have to be analysed for which no suitable tools are available. These new types of data can be represented and treated as constraints, allowing a set of data to be represented through equations, inequations and Boolean combinations of both. To this end, constraint databases were defined and some prototypes were developed. Since there are aspects that can be improved, we propose a new architecture called labelled object-relational constraint database (LORCDB). This provides more expressiveness, since the database is adapted in order to support more types of data, instead of the data having to be adapted to the database. In this paper, the projection operator of SQL is extended so that it works with linear and polynomial constraints and variables of constraints. In order to optimize query evaluation efficiency, some strategies and algorithms have been used to obtain an efficient query plan. Most work on constraint databases uses spatiotemporal data as case studies. However, this paper proposes model-based diagnosis since it is a highly potential research area, and model-based diagnosis permits more complicated queries than spatiotemporal examples. Our architecture permits the queries over constraints to be defined over different sets of variables by using symbolic substitution and elimination of variables.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-0

Applying Constraint Databases in the Determination of Potential Minimal Conflicts to Polynomial Model-Based Diagnosis

Model-based Diagnosis allows the identification of the parts which fail in a system. The models are based on the knowledge of the system to diagnose, and may be represented by constraints associated to the components. The variables of these constraints can be observable or non-observable, depending on the situation of the sensors. In order to obtain the potential minimal diagnosis in a system, an important issue is related to finding out the potential minimal conflicts in an efficient way. We consider that Constraint Databases represent an excellent option in order to solve this problem in complex systems. In this work we have used a novel logical architecture of Constraint Databases which has allowed obtaining these potential conflicts by means of the corresponding queries. Moreover, we have considered Gröbner Bases as a projection operator to obtain the potential minimal conflicts of a system. The first results obtained on this work, which are shown in a heat exchangers example, have been very promising.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

NMUS: Structural Analysis for Improving the Derivation of All MUSes in Overconstrained Numeric CSPs

Models are used in science and engineering for experimentation, analysis, model-based diagnosis, design and planning/sheduling applications. Many of these models are overconstrained Numeric Constraint Satisfaction Problems (NCSP), where the numeric constraints could have linear or polynomial relations. In practical scenarios, it is very useful to know which parts of the overconstrained NCSP instances cause the unsolvability. Although there are algorithms to find all optimal solutions for this problem, they are computationally expensive, and hence may not be applicable to large and real-world problems. Our objective is to improve the performance of these algorithms for numeric domains using structural analysis. We provide experimental results showing that the use of the different strategies proposed leads to a substantially improved performance and it facilitates the application of solving larger and more realistic problems.Ministerio de Educación y Ciencia DIP2006-15476-C02-0

La predicción del abandono terapéutico a través de variables de construcción de significado: un estudio con clientes de la práctica privada

Falta palabras claveEsta Tesis está destinada a mejorar la atención a clientes que demandan asistencia terapéutica en consultas privadas. Un número relativamente importante de ellos abandona la terapia antes de su finalización y el interés de este estudio es encontrar qué factores de su demanda terapéutica y su sistema de construcción de significados pueden ser mediadores del abandono. El abandono del tratamiento es un proceso complejo, determinado por múltiples factores específicos del individuo, la sintomatología que éste padece, la terapia proporcionada por el profesional y el contexto terapéutico en el que se desarrolla. Aunque la inmensa mayoría de los autores comparten la idea de que el abandono es un fenómeno multideterminado, los estudios existentes se concentran en uno o muy pocos de los factores implicados. Este estudio se centra y se plantea qué factores están determinando en los clientes la adhesión terapéutica completa, y sí además, hay otros factores que influyen en el abandono del tratamiento como la sintomatología asociada al sujeto, variables de tipo socioeconómico, género, tipo demanda terapéutica, si han realizado un tratamiento terapéutico previo, tonos narrativos de su historia de vida, la influencia de los dilemas implícativos y formas de construcción propia de los sujetos de sus significados personales. En definitiva, entender como esas variables pueden predecir el abandono. Para ello se utilizaron las siguientes herramientas: a) la técnica de rejilla, que evalúa las dimensiones y estructura del significado personal; b) la escala de Síntomas de Derogatis (SCL-90-R) para evaluar sintomatología general; c) Entrevista de la historia de vida, que trata de un procedimiento que permite analizar los tonos narrativos, tanto de historias de vida formales como de sesiones terapéuticas; d) Historia clínica, protocolo de recogida de datos clínicos utilizado en la propia consulta. Los participantes del estudio son 220 sujetos. Son los casos atendidos la consulta privada COPSICA Psicólogos a lo largo de 8 años. Se realizaron regresiones binomiales y manovas para el análisis de los datos Las conclusiones de este estudio fueron que, probablemente, las temáticas relacionadas con los significados personales contribuyen a no abandonar la terapia, así como el tono narrativo positivo, pero no el negativo.. No hay evidencia de que la presencia de dilemas al inicio de la terapia sea un indicador de abandono ni que tengan más sintomatología que los que no presentan dilemas en ese momento. Además, la presencia o ausencia de dilemas es determinante para conseguir el cambio terapéutico. Por otro lado, el tipo de demanda no es un factor que determine la reducción de sintomatología producida por la terapia. Además el abandono no está ligado a una mayor sintomatología inicial. Aunque en general, podríamos decir que las condiciones sociodemográficas negativas predicen el abandono. También podemos afirmar que el abandono es un fenómeno complejo, relacionado con condiciones socioeconómicas desfavorables, a la experiencia terapéutica previa y a fenómenos cognitivos que supongan disponer de muchos significados y de significados rígido

Multi-criteria decision analysis for non-conformance diagnosis: A priority-based strategy combining data and business rules

Business process analytics and verification have become a major challenge for companies, especially when process data is stored across different systems. It is important to ensure Business Process Compliance in both data-flow perspectives and business rules that govern the organisation. In the verification of data-flow accuracy, the conformance of data to business rules is a key element, since essential to fulfil policies and statements that govern corporate behaviour. The inclusion of business rules in an existing and already deployed process, which therefore already counts on stored data, requires the checking of business rules against data to guarantee compliance. If inconsistency is detected then the source of the problem should be determined, by discerning whether it is due to an erroneous rule or to erroneous data. To automate this, a diagnosis methodology following the incorporation of business rules is proposed, which simultaneously combines business rules and data produced during the execution of the company processes. Due to the high number of possible explanations of faults (data and/or business rules), the likelihood of faults has been included to propose an ordered list. In order to reduce these possibilities, we rely on the ranking calculated by means of an AHP (Analytic Hierarchy Process) and incorporate the experience described by users and/or experts. The methodology proposed is based on the Constraint Programming paradigm which is evaluated using a real example. .Ministerio de Ciencia y Tecnología RTI2018–094283-B-C3

Determination of Possible Minimal Conflict Sets Using Constraint Databases Technology and Clustering

Model-based Diagnosis allows the identification of the parts which fail in a system. The models are based on the knowledge of the system to diagnose, and can be represented by constraints associated to components. Inputs and outputs of components are represented as variables of those constraints, and they can be observable and non-observable depending on the situation of sensors. In order to obtain the minimal diagnosis in a system, an important issue is to find out the possible minimal conflicts in an efficient way. In this work, we propose a new approach to automate and to improve the determination of possible minimal conflict sets. This approach has two phases. In the first phase, we determine components clusters in the system in order to reduce drastically the number of contexts to consider. In the second phase, we construct a reduced context network with the possible minimal conflicts. In this phase we use Gröbner bases reduction.A novel logical architecture of Constraint Databases is used to store the model, the components clusters and possible minimal conflict sets. The necessary information in each phase is obtained by using a standard query language.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Determination of an optimal test points allocation for business process analysis

The management and automation of business processes have become an essential task within IT organizations. Diagnosis enables fault isolation in a business process. The diagnosis process uses a set of test points (observations) and a model in order to explain a wrong behavior. In this work, a series of algorithms to allocate test points are presented. The key idea is to improve the diagnosability, improving the computational complexity for isolating faults in a system. The methodology is based on constraint programming.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Improving the Diagnosability of Business Process Management Systems Using Test Points

The management and automation of business processes have become an essential task within IT organizations, where the diagnosis is a very important issue, since it enables fault isolation in a business process. The diagnosis process uses a set of test points (observations) and a model in order to explain a wrong behavior. In this work, an algorithm to allocate test points is presented, where the key idea is to improve the diagnosability, getting a better computational complexity for isolating faults in the activities of business processesJunta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Diagnosis applied CSP based on models

En las ´ultimas d´ecadas, parte de la comunidad cient´ıfica ha dedicado sus esfuerzos al desarrollo de una metodolog´ıa para la diagnosis de sistemas desde el campo de la Inteligencia Artificial. Dicha metodolog´ıa se denomina diagnosis basada en modelos, y cubre un amplio abanico de posibilidades. Se parte de un modelo expl´ıcito del sistema a diagnosticar y a partir de ´el se razona sobre la identificaci´on de los subsistemas que generan fallos, utilizando para ello los valores de las entradas proporcionadas y las salidas captadas del sistema. En cualquier proceso de producci´on o desarrollo es importante tener un control sobre los fallos en componentes o procesos. La diagnosis permite controlar estas irregularidades, lo que conlleva a los sistemas que la incorporan una mayor seguridad y reducci´on de costos. Algunos modelos utilizados en ingenier´ıa se han basado en la programaci´on l´ogica con restricciones (CLP) para obtener la diagnosis de un sistema. En este art´ıculo proponemos la metodolog´ıa necesaria para poder plantear la diagnosis de un sistema como un problema de satisfacci´on de restricciones (CSP). De esta forma, ser´a posible incorporar al proceso de generaci´on de la diagnosis de un sistema, los avances y optimizaciones que se han alcanzado en el campo de la b´usqueda de soluciones para problemas CSP. Plantear un problema de diagnosis de esta forma abre tambi´en la posibilidad de aplicar la diagnosis a otros campos, como por ejemplo la diagnosis del software. La diagnosis del software permite identificar y localizar el origen de los errores de un desarrollo software. Un programa tendr´a un error si no existe concordancia entre los resultados especificados como correctos y los resultados observados tras la ejecuci´on.In the last decades, model-based diagnosis has been an active research topic for the Artificial Intelligence community. It uses the explicit model of a system, the system inputs and the measured system outputs, in order to identify the subsystems that can generate faults. The system or the process that incorporates diagnosis may reduce costs and provide more security. Some models used in engineering are based on constraint logic programming (CLP) in order to obtain the system diagnosis. In this paper we propose a methodology for the system diagnosis as a constraint satisfaction problem (CSP). Using this methodology it is possible to incorporate, the advances and optimizations achieved for the search of solutions in CSP. This methodology also offers the possibility of applying diagnosis to other areas, such as software diagnosis. Software diagnosis allows the identification of the program bugs. A bug occurs when there is not matching between the specified results and the observed results after a program execution.Ministerio de Ciencia y Tecnología DPI2000-0666-C02-0

CSP and Restricted Databases

Las Bases de Datos Restrictivas se originaron ante la necesidad de representar de forma m´as compacta y modular datos de gran tama˜no. De esta forma, y como medio para tratar datos continuos como es el caso de los espacio-temporales, se opt´o por tratar la informaci´on como restricciones almacenadas en una base de datos. Gracias a esta forma de tratar las restricciones, se facilita la construcci´on y el modelado de problemas de satisfacci´on de restricciones (CSP) y su posterior resoluci´on. En este art´ıculo, se realiza un recorrido por las distintas razones, metodolog´ıas y herramientas que han ayudado al desarrollo de las Bases de Datos Restrictivas. Junto a dicho estudio, se lleva a cabo un an´alisis de sus deficiencias y de los posibles aspectos a mejorar. Para aumentar la habilidad en la construcci´on de modelos, y ayudando a la resoluci´on de problemas de satisfacci´on de restricciones (CSP), se ofrece una arquitectura de implementaci´on modular, con las ventajas que eso conlleva. Para finalizar, se presenta un ejemplo que aclara las razones que han movido al desarrollo de nuestra propuesta.Constraint Databases were proposed because it was necessary to represent infinite relations in a more modular and compact way. In this way, Constraint Databases were used to handle continuous data, like spatio-temporal, and to enrich both the data model and the queries with constraints. It allows us to handle these constraints and it makes easier to construct and model the Constraint Satisfaction Problems (CSP) when we want to evaluate these queries. In this paper, we carry out a study of the different reasons, methodologies and tools that have helped to the development of Constraint Databases. Also, we present a study of some defects and how to improve them. To help us in the CSP construction, we show a modular framework, with all the advantages that it implies. Finally, we show an example to understand better the reasons that have helped to the development of our system.Ministerio de Ciencia y Tecnología DPI2000-0666-C02-0