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

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

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

Distributed Model-Based Diagnosis using Object-Relational Constraint Databases

This work presents a proposal to diagnose distributed systems utilizing model-based diagnosis using distributed databases. In order to improve aspects as versatility, persistence, easy composition and efficiency in the diagnosis process we use an Object Relational Constraint Database (ORCDB). Thereby we define a distributed architecture to store the behaviour of components as constraints in a relational database to diagnose a distributed system. This work proposes an algorithm to detect which components fail when their information is distributed in several databases, and all the information is not available in a global way. It is also offered a proposal to define, in execution time, the allocation of the sensors in a distributed system.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

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

Querying a Polynomial Object-Relational Constraint Database in Model-Based Diagnosis

Many papers related to Constraint Databases (CDBs) theories exist, including proposals that present frameworks for the treatment of constraints as a new data type. Our proposal presents a new way of storing and manipulating constraints as a usual data, and of making queries about the constraint variables derived from an Object-Relational Constraint Database (ORCDB). In this work, the constraints stored in an ORCDB are only polynomial equality constraints. The proposal is based on Gr¨obner bases, constraint consistency and constraint optimisation techniques. Most works in CDB use spatial-temporal data as a case study, however this work presents an emergent engineering domain, that of fault diagnosis.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Improving the determination of minimal hitting sets in model-based diagnosis using constraint databases

In model-based diagnosis, minimal hitting sets are usually used to identify which components may fail in a system. This work presents a set of algorithms to improve the determination of all Minimal Hitting Sets. Our proposal uses the minimal conflict sets to obtain, in an efficient way, the diagnosis of a system. The improvement consists of three algorithms which analyse only the relevant options. This proposal builds an equivalent system in order to obtain all minimal hitting sets depending on the location of the sensors. At the same time, all the information of the process is stored in a Constraint Database, keeping the information persistent and recoverable. Some empirical results are presented in order to show how the proposal improves the process in order to obtain all minimal hitting sets.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Constraint Databases Technology for Polynomial Models 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 they can be represented by constraints associated to the components. The variables including in these con straints can be observable or non-observable, depending on the situa tion of sensors. In order to obtain the minimal diagnosis in a system, an important issue is related to find out the minimal possible conflicts in an efficient way. We consider that Constraint Databases represent an excellent approach in order to solve this problem in complex sys tems, where a tuple in a relational database could be replaced by a conjunction of constraints. In this work we have used a novel logical architecture of Con straint Databases which has allowed us to obtain these possible min imal conflicts by means of a standard query language though the in formation is stored in a conventional relational database. Moreover, we have considered Grobner bases as a projection operator to obtain ¨ the minimal possible conflicts of a system.Ministerio de Ciencia y Tecnología DPI2003-07146-C02-0

Current understanding of genetic polymorphisms as biomarkers for risk of biological complications in implantology

In the last decade, multiple studies have been published that analyze the relationship between the risk of experiencing biological complications with implants and the presence of certain types of genetic polymorphisms. In the present report, we analyze the controversies that have arisen from this important area of investigation and synthesize the most prominent aspects of knowledge related to this possible etiopathogenic relationship. For this review, the biomedical databases PubMed-Medline, SciELO, and DOAJ were used. Different search strategies were employed, from which 298 articles initially emerged. After refinement of the search, 55 articles published between 2002 and 2018 were finally selected based on relevance. In certain population groups, there is evidence to support that about a dozen polymorphisms could in some way be related to biological complications in implantology. Indeed, the results may vary according to the ethnic origin of the population studied. Most of the published investigations are initial studies reporting small sample sizes and utilizing different study group homogenization methods. We are still at a preliminary stage of our understanding and development with regard to these types of biomarkers. The interesting results identified indicate that new investigations will be necessary to eliminate the biases observed in some studies and to homogenize the research groups. In order to clarify the controversies surrounding the current knowledge in this field, we believe that it will be necessary to employ larger study groups and search for possible synergistic effects between different polymorphisms