Domain-Specific Language for Coordination patterns

The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language

Slicing functional programs by calculation

Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually targeting either the imperative or the object oriented paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to (sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies’ structure, we resort to standard program calculation strategies, based on the so-called Bird- Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general alternative to slicing functional programs

Analysis of computing open source systems

Graphical user interfaces (GUIs) are critical components of today's open source software. Given their increased relevance, the correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing open source systems. We use static analysis techniques to generate models of the user interface behavior from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particular type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface's quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Detection of road accident accumulation zones with a visual analytics approach

Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.

Development of autonomous maintenance in a furniture company

This article presents a work performed in the maintenance department of a furniture company in Portugal, in order to develop and implement autonomous maintenance. The main objective of the project was related to the objective to increase and make effective the autonomous maintenance tasks performed by production operators, and in this way avoiding unplanned downtime due to equipment failures. Although some autonomous maintenance tasks were already carried out within the company, a preliminary study revealed weaknesses in the application of this tool. In the initial phase of this pilot project, the main problems encountered at the level of autonomous maintenance were related to the lack of time to carry out these tasks, showing that the stipulated procedures were far from the real needs of the company. To solve these problems a pilot project was conducted, making several changes in the performance of autonomous maintenance tasks, making them standard and adapted to reality of each production line. There was a general improvement in the factory indicators, and essentially there was a behavioral change, since the operators felt that their opinions were taking into account and began to understand the importance of small tasks performed by them.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Construir uma comunidade de aprendizagem: a aprendizagem cooperativa de conteúdos multimédia fomentada por um ambiente promotor da valorização do conhecimento

Relatório de estágio de mestrado em Ensino de Informática

Cost-effective and lightweight mobile units for MixAR: A comparative trial among different setups

Cultural heritage has arousing the interest of the general public (e.g. tourists), resulting in the increasing number of visitations to archaeological sites. However, many buildings and monuments are severely damaged or completely destroyed, which doesn’t allow to get a full experience of “travelling in time”. Over the years, several Augmented Reality (AR) approaches were proposed to overcome these issues by providing three-dimensional visualization of reconstructed ancient structures in situ. However, most of these systems were made available through heavy and expensive technological bundles. Alternatively, MixAR intends to be a lightweight and cost-effective Mixed Reality system which aims to provide the visualization of virtual ancient buildings reconstructions in situ, properly superimposed and aligned with real-world ruins. This paper proposes and compares different AR mobile units setups to be used in the MixAR system, with low-cost and lightweight requirements in mind, providing different levels of immersion. It was propounded four different mobile units, based on: a laptop computer, a single-board computer (SBC), a tablet and a smartphone, which underwent a set of tests to evaluate their performances. The results show that mobile units based on laptop computer and SBC reached a good overall performance while mobile units based on tablet and smartphone did not meet such a satisfactory result even though they are acceptable for the intended use.

MixAR mobile prototype: visualizing virtually reconstructed ancient structures in situ

Archeology and related areas have a special interest on cultural heritage sites since they provide valuable information about past civilizations. However, the ancient buildings present in these sites are commonly found in an advanced state of degradation which difficult the professional/expert analysis. Virtual reconstructions of such buildings aim to provide a digital insight of how these historical places could have been in ancient times. Moreover, the visualization of such models has been explored by some Augmented Reality (AR) systems capable of providing support to experts. Their compelling and appealing environments have also been applied to promote the social and cultural participation of general public. The existing AR solutions regarding this thematic rarely explore the potential of realism, due to the following lacks: the exploration of mixed environments is usually only supported for indoors or outdoors, not both in the same system; the adaptation of the illumination conditions to the reconstructed structures is rarely addressed causing a decrease of credibility. MixAR [1] is a system concerned with those challenges, aiming to provide the visualization of virtual buildings augmented upon real ruins, allowing soft transitions among its interiors and exteriors and using relighting techniques for a faithful interior illumination, while the user freely moves in a given cultural heritage site, carrying a mobile unit. Regarding the focus of this paper, we intend to report the current state of MixAR mobile unit prototype, which allows visualizing virtual buildings – properly aligned with real-world structures – based on user's location, during outdoor navigation. In order to evaluate the prototype performance, a set of tests were made using virtual models with different complexities.

Unfuzzying fuzzy parsing

Dissertação de Mestrado em Engenharia Informática

Implementation of a lean six sigma project in a production line

Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.

Clustering barotrauma patients in ICU–A data mining based approach using ventilator variables

Lecture Notes in Computer Science, 9273