Sistema pericial para o estudo de composição de betões

O betão é o material de construção feito pelo Homem mais utilizado no mundo. A sua composição é um processo complexo que exige um conhecimento teórico sólido e muita experiência prática, pelo que poucas pessoas estão habilitadas para o fazer e são muito requisitadas. No entanto não existe muita oferta actual de software que contemple alguns dos aspectos importantes da composição do betão, nomeadamente para o contexto europeu. Nesse sentido, foi desenvolvido um sistema de apoio à decisão chamado Betacomp, baseado num sistema pericial, para realizar estudos de composição de betão. Este contempla as normas legais portuguesas e europeias, e a partir da especificação do betão apresenta toda a informação necessária para se produzir um ensaio de betão. A aquisição do conhecimento necessário ao sistema contou com a colaboração de um especialista com longa e comprovada experiência na área da formulação e produção do betão, tendo sido construída uma base de conhecimento baseada em regras de produção no formato drl (Drools Rule Language). O desenvolvimento foi realizado na plataforma Drools.net, em C# e VB.net. O Betacomp suporta os tipos de betão mais comuns, assim como adições e adjuvantes, sendo aplicável numa grande parte dos cenários de obra. Tem a funcionalidade de fornecer explicações sobre as suas decisões ao utilizador, auxiliando a perceber as conclusões atingidas e simultaneamente pode funcionar como uma ferramenta pedagógica. A sua abordagem é bastante pragmática e de certo modo inovadora, tendo em conta parâmetros novos, que habitualmente não são considerados neste tipo de software. Um deles é o nível do controlo de qualidade do produtor de betão, sendo feito um ajuste de compensação à resistência do betão a cumprir, proporcional à qualidade do produtor. No caso dos produtores de betão, permite que indiquem os constituintes que já possuem para os poderem aproveitar (caso não haja impedimentos técnicos) , uma prática muito comum e que permitirá eventualmente uma aceitação maior da aplicação, dado que reflecte a forma habitual de agir nos produtores.

Analisi della qualità dei dati in un’enterprise architecture utilizzando un sistema d’inferenza.

Lo scopo della tesi è definire un modello e identificare un sistema d’inferenza utile per l’analisi della qualità dei dati. Partendo da quanto descritto in ambito accademico e business, la definizione di un modello facilita l’analisi della qualità, fornendo una descrizione chiara delle tipologie di problemi a cui possono essere soggetti i dati. I diversi lavori in ambito accademico e business saranno confrontati per stabilire quali siano i problemi di qualità più diffusi, in modo da realizzare un modello che sia semplice e riutilizzabile. I sistemi d’inferenza saranno confrontati a livello teorico e pratico per individuare lo strumento più adatto nell’analisi della qualità dei dati in un caso applicativo. Il caso applicativo è caratterizzato da requisiti funzionali e non; il principale requisito funzionale è l’individuazione di problemi di qualità nei dati, mentre quello non funzionale è l’ usabilità dello strumento, per permettere ad un qualunque utente di esprimere dei controlli sulla qualità. Il caso applicativo considera dati di un’enterprise architecture reale ed è stato fornito dall’azienda Imola Informatica.

Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

CloudMPL:a domain specific language for describing management policies for an autonomic cloud infrastructure

To benefit from the advantages that Cloud Computing brings to the IT industry, management policies must be implemented as a part of the operation of the Cloud. Among others, for example, the specification of policies can be used for the management of energy to reduce the cost of running the IT system or also for security policies while handling privacy issues of users. As cloud platforms are large, manual enforcement of policies is not scalable. Hence, autonomic approaches for management policies have recently received a considerable attention. These approaches allow specification of rules that are executed via rule-engines. The process of rules creation starts by the interpretation of the policies drafted by high-rank managers. Then, technical IT staff translate such policies to operational activities to implement them. Such process can start from a textual declarative description and after numerous steps terminates in a set of rules to be executed on a rule engine. To simplify the steps and to bridge the considerable gap between the declarative policies and executable rules, we propose a domain-specific language called CloudMPL. We also design a method of automated transformation of the rules captured in CloudMPL to the popular rule-engine Drools. As the policies are changed over time, code generation will reduce the time required for the implementation of the policies. In addition, using a declarative language for writing the specifications is expected to make the authoring of rules easier. We demonstrate the use of the CloudMPL language into a running example extracted from a management energy consumption case study.

A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.