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

Optimisation of operating conditions in batch for more sustainable continuous process transposition

Implementation of exothermic and fast reactions requires a perfect temperature control to avoid thermal runaway and in most cases to limit by-products production. In order to fit with the heat removal capacity of common devices, expensive strategies are currently used to slow down this kind of reactions in order to avoid a strong temperature increase such as reactants dilution. Within the concept of process intensification, industries could move towards more sustainable process by reducing technology constraints to the benefit of chemistry. For that purpose, a two-step methodology is implemented. The first step consists in the optimisation of the operating conditions only based on stoichio-chemical scheme and kinetic laws. This is carried out by adjusting temperature profile and feeding rate strategy in a batch operation. Then a design for a continuous process is proposed, trying to approach the optimal batch operating conditions. This methodology is applied to the linear alkylbenzene sulfonation

Constraint Databases and Geographic Information Systems

Constraint databases and geographic information systems share many applications. However, constraint databases can go beyond geographic information systems in efficient spatial and spatiotemporal data handling methods and in advanced applications. This survey mainly describes ways that constraint databases go beyond geographic information systems. However, the survey points out that in some areas constraint databases can learn also from geographic information systems

Influence of solvent choice on the optimisation of a reaction–separation operation : application to a Beckmann rearrangement reaction

In pharmaceutical syntheses, the solvent choice generally represents a complex design step. Traditionally, this choice is operated according to criteria connected with the reaction step and without any consideration on the following separation steps. The purpose of this study is to highlight the benefits of a global approach of optimisation for the solvent determination. In this way, an optimisation framework dedicated to global synthesis is applied to a simple reaction–separation operation integrating a Beckmann rearrangement reaction, leading to interesting solvent choices

COSMA - multi-participant NL interaction for appointment scheduling

We discuss the use of NL systems in the domain of appointment scheduling. Appointment scheduling is a problem faced daily by many people and organizations, and typically solved using communication in natural language. In general, cooperative interaction between several participants is required whose calendar data are distributed rather than centralized. In this distributed multi-agent environment, the use of NL systems makes it possible for machines and humans to cooperate in solving scheduling problems. We describe the COSMA (Cooperative Schedule Managament Agent) system, a secretarial assistant for appointment scheduling. A central part of COSMA is the reusable NL core system DISCO, which serves, in this application, as an NL interface between an appointment planning system and the human user. COSMA is fully implemented in Common Lisp and runs on Unix Workstations. Our experience with COSMA shows that it is a plausible and useful application for NL systems. However, the appointment planner was not designed for NL communication and thus makes strong assumptions about sequencing of domain actions and about the error-freeness of the communication. We suggest that further improvements of the overall COSMA functionality, especially with regard to flexibility and robustness, be based on a modified architecture

Deep Learning and Music Adversaries

OA Monitor ExerciseOA Monitor ExerciseAn {\em adversary} is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative. Recent work builds adversaries for deep learning systems applied to image object recognition, which exploits the parameters of the system to find the minimal perturbation of the input image such that the network misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the input to the systems is magnitude spectral frames, which requires special care in order to produce valid input audio signals from network-derived perturbations. For two different train-test partitionings of two benchmark datasets, and two different deep architectures, we find that this adversary is very effective in defeating the resulting systems. We find the convolutional networks are more robust, however, compared with systems based on a majority vote over individually classified audio frames. Furthermore, we integrate the adversary into the training of new deep systems, but do not find that this improves their resilience against the same adversary

A distributed SDP-based algorithm for large noisy anchor-free graph realization

Master'sMASTER OF SCIENC

Model-Driven Engineering for Constraint Database Query Evaluation

Data used in applications such as CAD, CAM or GIS are complex, but the techniques developed for their treatment and stor age are not adapted enough to their needs. Examples of these types of data are spatiotemporal, scientific, economic or industrial information, in which data has not a single value because is defined by parameters, variables, functions, equations . . .. These complex data cannot be repre sented nor evaluated with the relational algebra types, then a new, more complex, data type is needed, the Constraint type. Constraint Databases were defined and implemented in order to handle this type of constraint data. When a Constraint Database is implemented, different configura tion parameters can be set up, depending on which database manager is going to be used, which constraint programming tool is going to solve the query evaluation, or which type of constraints can be involved. When some of these parameters are changed, the implementation that supports the evaluation of queries over constraints have to be changed too. For this reason, we propose the use of Model-Driven Engineering to model the queries over Constraint Databases in an independent way of the im plementation and the techniques used to evaluate the queries.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-13714Ministerio de Ciencia y Tecnología TIN2010- 21744-C02-0