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

ORIGIN: metal creation and evolution from the cosmic dawn

Herder, Jan-Willem den et al.ORIGIN is a proposal for the M3 mission call of ESA aimed at the study of metal creation from the epoch of cosmic dawn. Using high-spectral resolution in the soft X-ray band, ORIGIN will be able to identify the physical conditions of all abundant elements between C and Ni to red-shifts of z = 10, and beyond. The mission will answer questions such as: When were the first metals created? How does the cosmic metal content evolve? Where do most of the metals reside in the Universe? What is the role of metals in structure formation and evolution? To reach out to the early Universe ORIGIN will use Gamma-Ray Bursts (GRBs) to study their local environments in their host galaxies. This requires the capability to slew the satellite in less than a minute to the GRB location. By studying the chemical composition and properties of clusters of galaxies we can extend the range of exploration to lower redshifts (z-0.2). For this task we need a high-resolution spectral imaging instrument with a large field of view. Using the same instrument, we can also study the so far only partially detected baryons in the Warm-Hot Intergalactic Medium (WHIM). The less dense part of the WHIM will be studied using absorption lines at low redshift in the spectra for GRBs. The ORIGIN mission includes a Transient Event Detector (coded mask with a sensitivity of 0.4 photon/cm2/s in 10 s in the 5–150 keV band) to identify and localize 2000 GRBs over a five year mission, of which -65 GRBs have a redshift > 7. The Cryogenic Imaging Spectrometer, with a spectral resolution of 2.5 eV, a field of view of 30 arcmin and large effective area below 1 keV has the sensitivity to study clusters up to a significant fraction of the virial radius and to map the denser parts of the WHIM (factor 30 higher than achievable with current instruments). The payload is complemented by a Burst InfraRed Telescope to enable onboard red-shift determination of GRBs (hence securing proper follow up of high-z bursts) and also probes the mildly ionized state of the gas. Fast repointing is achieved by a dedicated ControlledMomentum Gyro and a low background is achieved by the selected low Earth orbit.The team likes to express its appreciation for the support of Astrium UK for the present study.Peer Reviewe

Complejidades de la representación en enseñanza y aprendizaje del álgebra

Efectuar una representación mental sobre conceptos e ideas algebraicas para posteriormente transferirlos a estudiantes que se inician en el aprendizaje del álgebra parece ser parte de un proceso cognitivo complejo por el que los docentes deben pasar para construir conocimiento y comunicar saber. Los resultados en el rendimiento escolar de los estudiantes que tal proceso genera, frecuentemente por debajo de lo esperado, hacen suponer dificultades en algunos aspectos cognitivos del pensamiento algebraico involucrados en la enseñanza y el aprendizaje, por lo que consideramos pertinente el desarrollo de un estudio guiado por dos objetivos: 1)Estudiar la modificabilidad estructural cognitiva de los alumnos que se inician en el estudio del álgebra, a partir de las distintas representaciones que utiliza el profesor al explicar temas algebraicos. Y 2) Analizar cómo se expresa el profesor al explicar ideas y conceptos de álgebra, particularmente las representaciones verbales y escritas que utiliza en el salón de clase. La experiencia de aprendizaje mediada (EAM), elemento focal en la Teoría de la Modificabiliad Estructural Cognitiva, será el recurso para estudiar la representación, objeto de estudio en este anteproyecto

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

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

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

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