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.

On the impact of overlapping access points in detecting node encounters

Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Fishing territoriality and diversity between the ethnic populations Ashaninka and Kaxinawá ,Breu river, Brazil/Peru

This study describes the diversity and the subsistence fishing territoriality of traditional populations of a village Ashaninka and two Kaxinawá living at the margins of Breu River (Brasil/Peru). In general, samplings in the dwellings were carried out late in the afternoon, as the fishermen arrived in the village. The data were analysed in an exploratory way through the index of pondered dominance (ID%), by analysis of variance and by a correspondence analysis in order to determine the associations of the fish species and the fishing spots between the villages of the Indigenous Reserve. The results of the analysis of variance demonstrated that differences exist between the fish diversities of the catches. However, post-hoc tests only detected differences in diversities between the hand fishhook and the other fishing gears (bow and arrow, castnets and rotenone tingui). Although the use of bow and arrow resulted in a low capture (Kg), this fishing strategy is associated with a high fishing diversity, in terms of number of species. These results demonstrate that there is no overlap in the frequency of the visits to the fishing spots between the Ashaninka and Kaxinawá populations. This pattern is the same found for the correspondence analysis for the fish species, which describes the relationship between the deep pools environments exploited by the fishermen Ashaninka and Kaxinawá of Mourão. These ethnic populations still continue to maintain a strong cultural and cosmological tradition, with their territories defined in an informal way of the upper Juruá area.

A geographic opportunistic forwarding strategy for vehicular named data networking

Studies in Computational Intelligence, 616

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Categorização do consumo de energia em sistemas de povoamento de Data Warehouses

Os recursos computacionais exigidos durante o processamento de grandes volumes de dados durante um processo de povoamento de um data warehouse faz com que a necessidade da procura de novas implementações tenha também em atenção a eficiência energética dos diversos componentes processuais que integram um qualquer sistema de povoamento. A lacuna de técnicas ou metodologias para categorizar e avaliar o consumo de energia em sistemas de povoamento de data warehouses é claramente notória. O acesso a esse tipo de informação possibilitaria a construção de sistemas de povoamento de data warehouses com níveis de consumo de energia mais baixos e, portanto, mais eficientes. Partindo da adaptação de técnicas aplicadas a sistemas de gestão de base de dados para a obtenção dos consumos energéticos da execução de interrogações, desenhámos e implementámos uma nova técnica que nos permite obter os consumos de energia para um qualquer processo de povoamento de um data warehouse, através da avaliação do consumo de cada um dos componentes utilizados na sua implementação utilizando uma ferramenta convencional. Neste artigo apresentamos a forma como fazemos tal avaliação, utilizando na demonstração da viabilidade da nossa proposta um processo de povoamento bastante típico em data warehouses – substituição encadeada de chaves operacionais -, que foi implementado através da ferramenta Kettle.

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

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

Lecture Notes in Computer Science, 9273

Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.

A case study of product usability of a pelvic device used by children with neuromotor impairments

On assistive technology targeted for people with activity limitations and participation, usability issues becomes an essential tool to ensure that the product has the appropriate ergonomics characteristics, in other words, ensure that it fits the specific user´s needs. The aim of this study was to analyze the usability of an adaptive seating device for children with neuromotor impairments, by using kinematic indicators of the reaching movement. The study sample consisted of 13 children with associated neurologic conditions. The tests were developed by using a wooden bench height adjustable, integrated with the adaptive seating device under study, and a system to capture three-dimensional image, called Qualisys Track Manager. The following reaching kinematics variables were measured: maximum reaching velocity, movement duration, index of curvature, and unit movements. It was found that the use of the adaptive seating device had a positive impact on upper limb function in children with neuromotor impairments. It was also noticed an improvement in the reaching movement kinematics, which was statistical significant for the index of curvature and unit movements. As main conclusions, it is possible to point out some positive effects that the product under study seems to have on users' movements, such as the improved movement quality of the upper limb, which could mean a better postural adjustments and higher trunk postural control. By identifying new measures of usability in terms of effectiveness and efficiency for the analyzeddevice, the results obtained may serve also as performance indicators, providing new data that may help to improve the product and eventually modifying it, in order to turn it more compatible with the needs of the considered target population.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

The greener grass: da autorrepresentação em Alanis Morissette

Tese de Doutoramento em Ciências da Literatura - Especialidade em Teoria da Literatura