An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Subjective versus objective stress in noncritically ill hospitalized and outpatient adult men

A cross-sectional study of 120 subjects was performed with the purpose of evaluating stress hormones and emotional stress (anxiety) in outpatient and hospitalized subjects. The aims were to determine the degree of objective stress, as well as to correlate this finding with subjective findings, estimated using Beck's Anxiety Inventory.. METHOD: Three populations were investigated, namely outpatient clinical cases (Group I, n = 30), hospitalized clinical individuals (Group II, n = 30), and hospitalized surgical candidates (Group III, n = 30). Controls (Group IV, n = 30) were healthy volunteers who were health-care professionals and students. To avoid hormone interactions, only men were enrolled in all groups. All hospitalized subjects were tested on admission and before therapeutic interventions. Fasting epinephrine, norepinephrine, and cortisol were measured in the morning, and Beck's Anxiety Inventory was adminstered by a trained psychologist. RESULTS: The 3 patient groups displayed higher anxiety levels than the controls. Hormone concentrations did not present remarkable changes and did not correlate with subjective stress (anxiety). CONCLUSIONS: 1) Subjective disorders (as determined with Beck's Anxiety Inventory ) were a common finding in both outpatient and hospitalized populations, without differences between the various groups; 2) Objective stress (as determined by elevated hormone levels) was more difficult to confirm-findings rarely exceeded the reference range; 3) Correlation between the two variables could not be demonstrated; 4) Further studies are necessary to define stress quantification and interpretation in patient populations, especially in relationship with nutritional diagnosis and dietetic prescription.

Monitoring liquidity risk at BPI GA

Field lab: Business project

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Self-monitoring of freeze–thaw damage using triphasic electric conductive concrete

The effect of freeze–thaw cycles on concrete is of great importance for durability evaluation of concrete structures in cold regions. In this paper, damage accumulation was studied by following the fractional change of impedance (FCI) with number of freeze–thaw cycles (N). The nano-carbon black (NCB), carbon fiber (CF) and steel fiber (SF) were added to plain concrete to produce the triphasic electrical conductive (TEC) and ductile concrete. The effects of NCB, CF and SF on the compressive strength, flexural properties, electrical impedance were investigated. The concrete beams with different dosages of conductive materials were studied for FCI, N and mass loss (ML), the relationship between FCI and N of conductive concrete can be well defined by a first order exponential decay curve. It is noted that this nondestructive and sensitive real-time testing method is meaningful for evaluating of freeze–thaw damage in concrete.

Innovative method for the continuous monitoring of concrete viscoelastic properties since early ages: concept and pilot experiments

The experimental evaluation of viscoelastic properties of concrete is traditionally made upon creep tests that consist in the application of sustained loads either in compression or in tension. This kind of testing demands for specially devised rigs and requires careful monitoring of the evolution of strains, whereas assuring proper load constancy. The characterization of creep behaviour at early ages offers additional challenges due to the strong variations in viscoelastic behaviour of concrete during such stages, demanding for several testing ages to be assessed. The present research work aims to assist in reducing efforts for continuous assessment of viscoelastic properties of concrete at early ages, by application of a dynamic testing technique inspired in methodologies used in polymer science: Dynamic Mechanical Analyses. This paper briefly explains the principles of the proposed methodology and exhibits the first results obtained in a pilot application. The results are promising enough to encourage further developments.

Monitoring the early stiffness development in epoxy adhesives for structural strengthening

The present work aimed to assess the early-age evolution of E-modulus of epoxy adhesives used for Fibre-Reinforced Polymer (FRP) strengthening applications. The study involved adapting an existing technique devised for continuous monitoring of concrete stiffness since casting, called EMM-ARM (Elasticity Modulus Measurement through Ambient Response Method) for evaluation of epoxy stiffness. Furthermore, monotonic tensile tests according to ISO standards and cyclic tensile tests were carried out at several ages. A comparison between the obtained results was performed in order to better understand the performance of the several techniques in the assessment of stiffness of epoxy resins. When compared to the other methodologies, the method for calculation of E-modulus recommended by ISO standard led to lower values, since in the considered strain interval, the adhesive had a non-linear stress–strain relationship. The EMM-ARM technique revealed its capability in clearly identifying the hardening kinetics of epoxy adhesives, measuring the material stiffness growth during the entire curing period. At very early ages the values of Young׳s modulus obtained with quasi-static tests were lower than the values collected by EMM-ARM, due to the fact that epoxy resin exhibited a significant visco-elastic behaviour.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

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.

Monitoring energy consumption in android applications

Dissertação de Mestrado em Engenharia Informática

Monitoring and analysis of queries in distributed databases

Dissertação de Mestrado em Engenharia Informática

Ergonomic analysis in a food packaging workplace

Work-related musculoskeletal disorders (WMSD) became one of the biggest health problems in the workplace and one of the main concerns of ergonomics and despite all the technical improvements manual handling is still an important risk factor for WMSD. The current study was performed with the main objective of conducting an ergonomic analysis in a workplace that consists in packaging products in a pallet, in a food distribution industry, also called picking. In this perspective, the aim of the study is to identify if the tasks performed by operators present any risk of WMSD and, if so, to suggest proposals for minimizing the associated effort. The methodologies of ergonomic risk assessment that were initially applied were the Risk Reckoner and the Manual Handling Assessment Chart (MAC). Subsequently, in order to, on the one hand, complement the analysis performed using the two methods previously mentioned, and, on the other hand, allow an assessment of two important risk factors associated with this activity (work postures and loads handling), two additional methodologies were also selected: the Revised NIOSH Lifting Equation and the Rapid Entire Body Assessment (REBA). In all the performed approaches, the tasks of palletizing at lower levels were identified as the ones that most penalize workers in what regards the risk of development of WMSD. All methodologies identified levels of risk that require an immediate or short-term ergonomic intervention, aiming at ensuring the safety and health of workers performing such activity. The implementation of measures designed to eliminate or minimize the risk may involve the allocation of significant human and material resources that is increasingly necessary to manage efficiently. Taking into account the complexity and variability of the developed tasks, it is recommended that such a decision can be preceded by a new study using more accurate risk assessment methodologies, such as those that use monitoring tools.

Ensino, aprendizagem e avaliação no Ensino Superior: Perspetivas e práticas

Tese de Doutoramento em Ciências da Educação - Especialidade de Desenvolvimento Curricular

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.