Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

Fast Mining of Interesting Phrases from Subsets of Text Corpora

We address the problem of mining interesting phrases from subsets of a text corpus where the subset is specified using a set of features such as keywords that form a query. Previous algorithms for the problem have proposed solutions that involve sifting through a phrase dictionary based index or a document-based index where the solution is linear in either the phrase dictionary size or the size of the document subset. We propose the usage of an independence assumption between query keywords given the top correlated phrases, wherein the pre-processing could be reduced to discovering phrases from among the top phrases per each feature in the query. We then outline an indexing mechanism where per-keyword phrase lists are stored either in disk or memory, so that popular aggregation algorithms such as No Random Access and Sort-merge Join may be adapted to do the scoring at real-time to identify the top interesting phrases. Though such an approach is expected to be approximate, we empirically illustrate that very high accuracies (of over 90%) are achieved against the results of exact algorithms. Due to the simplified list-aggregation, we are also able to provide response times that are orders of magnitude better than state-of-the-art algorithms. Interestingly, our disk-based approach outperforms the in-memory baselines by up to hundred times and sometimes more, confirming the superiority of the proposed method.

A primer for the Environmental Impact Assessment of mining at seafloor massive sulfide deposits

Seafloor massive sulfides (SMS) contain commercially viable quantities of high grade ores, making them attractive prospect sites for marine mining. SMS deposits may also contain hydrothermal vent ecosystems populated by high conservation value vent-endemic species. Responsible environmental management of these resources is best achieved by the adoption of a precautionary approach. Part of this precautionary approach involves the Environmental Impact Assessment (EIA) of exploration and exploitative activities at SMS deposits. The VentBase 2012 workshop provided a forum for stakeholders and scientists to discuss issues surrounding SMS exploration and exploitation. This forum recognised the requirement for a primer which would relate concepts underpinning EIA at SMS deposits. The purpose of this primer is to inform policy makers about EIA at SMS deposits in order to aid management decisions. The primer offers a basic introduction to SMS deposits and their associated ecology, and the basic requirements for EIA at SMS deposits; including initial data and information scoping, environmental survey, and ecological risk assessment. © 2013 Elsevier Ltd.

VentBase:Developing a consensus among stakeholders in the deep-sea regarding environmental impact assessment for deep-sea mining-A workshop report

Mining seafloor massive sulfides for metals is an emergent industry faced with environmental management challenges. These revolve largely around limits to our current understanding of biological variability in marine systems, a challenge common to all marine environmental management. VentBase was established as a forum where academic, commercial, governmental, and non-governmental stakeholders can develop a consensus regarding the management of exploitative activities in the deep-sea. Participants advocate a precautionary approach with the incorporation of lessons learned from coastal studies. This workshop report from VentBase encourages the standardization of sampling methodologies for deep-sea environmental impact assessment. VentBase stresses the need for the collation of spatial data and importance of datasets amenable to robust statistical analyses. VentBase supports the identification of set-asides to prevent the local extirpation of vent-endemic communities and for the post-extraction recolonization of mine sites. © 2013.

A primer for use of genetic tools in selecting and testing the suitability of set-aside sites protected from deep-sea seafloor massive sulfide mining activities

Seafloor massive sulfide (SMS) mining will likely occur at hydrothermal systems in the near future. Alongside their mineral wealth, SMS deposits also have considerable biological value. Active SMS deposits host endemic hydrothermal vent communities, whilst inactive deposits support communities of deep water corals and other suspension feeders. Mining activities are expected to remove all large organisms and suitable habitat in the immediate area, making vent endemic organisms particularly at risk from habitat loss and localised extinction. As part of environmental management strategies designed to mitigate the effects of mining, areas of seabed need to be protected to preserve biodiversity that is lost at the mine site and to preserve communities that support connectivity among populations of vent animals in the surrounding region. These "set-aside" areas need to be biologically similar to the mine site and be suitably connected, mostly by transport of larvae, to neighbouring sites to ensure exchange of genetic material among remaining populations. Establishing suitable set-asides can be a formidable task for environmental managers, however the application of genetic approaches can aid set-aside identification, suitability assessment and monitoring. There are many genetic tools available, including analysis of mitochondrial DNA (mtDNA) sequences (e.g. COI or other suitable mtDNA genes) and appropriate nuclear DNA markers (e.g. microsatellites, single nucleotide polymorphisms), environmental DNA (eDNA) techniques and microbial metagenomics. When used in concert with traditional biological survey techniques, these tools can help to identify species, assess the genetic connectivity among populations and assess the diversity of communities. How these techniques can be applied to set-aside decision making is discussed and recommendations are made for the genetic characteristics of set-aside sites. A checklist for environmental regulators forms a guide to aid decision making on the suitability of set-aside design and assessment using genetic tools. This non-technical primer document represents the views of participants in the VentBase 2014 workshop.

Integration of geochemical and biological modifications in mining areas: waters, sediments and diatoms

The development of mining activities over thousands of years in the region of Aljustrel is nowadays visible as a vast area of ore tailings, slag and host rocks of sulphides mineralization. The generation of acidic waters by the alteration of pyritic minerals - Acid Mine Drainage (AMD) - causes a significant impact on the river system both in the south of the village (Rib ª. Água Forte) and in the north of it (Rib ª. Água Azeda and Barranco do Farrobo), which is reflected in extremely low pH values (< 3) and high concentrations of As, Cd, Cu, Fe, Mn, Pb, Zn and sulphates. This study aimed to assess the environmental impacts extent, integrating geochemical (surface waters and stream sediments) and biological (diatoms) parameters. Three groups of sites were defined, based on sediments and water analysis, which integration with diatom data showed the same association of groups: Group 1- impacted, with acidic pH (1.9-5.1), high metal contents (0.4-1975 mg L-1) and Fe-Mg-sulphate waters, being metals more bioavailable in waters in cationic form (Me2+); mineralogically the sediments were characterized by phyllosilicates and sulphates/oxy-hydroxysulphate phases, easily solubilized, retaining a high amount of metals when precipitated; dominant taxon was Pinnularia aljustrelica (a new species); Group 2- slightly impacted, weak acid to neutral pH (5.0-6.8), metal contents not so high (0.2-25 mg L-1) and Fe-Mg-sulphate to Mg-chloride waters; dominant taxa were Brachysira neglectissima and Achnanthidium minutissimum; Group 3- unimpacted, alkaline pH (7.0-8.4), low metal contents (0-7 mg L-1) with Mg-chloride waters. In this group, metals were associated to the primary phases (e.g. sulphides), not so easily available; the existence of high chloride contents explained the presence of typical taxa of brackish/marine (e.g. Entomoneis paludosa) waters. Taxonomical aspects of the diatoms were studied (discovery of a new species: Pinnularia aljustrelica Luis, Almeida et Ector sp. nov.), as well as morphometric (size decrease of diatoms valves, as well as the appearance of deformed valves of Eunotia exigua in Group 1 and A. minutissimum in Group 2) and physiological (effective to assess the effects of metals/acidity in the photosynthetic efficiency through PAM Fluorometry) aspects. A study was carried out in an artificial river system (microcosm) that aimed to mimic Aljustrel’s extreme conditions in controlled laboratory conditions. The chronic effects of Fe, SO42- and acidity in field biofilms, inoculated in the artificial rivers, were evaluated as well as their contribution to the communities’ tolerance to metal toxicity, through acute tests with two metals (Cu and Zn). In general, the effects caused by low pH values and high concentrations of Fe and SO42- were reflected at the community level by the decrease in diversity, the predominance of acidophilic species, the decrease in photosynthetic efficiency and the increase of enzymatic (e.g. catalase, superoxide dismutase) and non-enzymatic activities (e.g. total glutathione and total phytochelatins). However, it was possible to verify that acidity performed a protective effect in the communities, upon Cu and Zn addition. A comparative study between Aljustrel mining area and New Brunswick mining area was carried out, both with similar mining and geological conditions, reflected in similar diatom communities in both mines, but in very different geographic and climatic areas.

The placebo and nocebo effects on peak minute power during incremental arm crank ergometry

This investigation aimed to explore the effects of inert sugar-free drinks described as either ‘performance enhancing’ (placebo) or ‘fatigue inducing’ (nocebo) on peak minute power (PMP;W) during incremental arm crank ergometry (ACE). Twelve healthy, non-specifically trained individuals volunteered to take part. A single-blind randomised controlled trial with repeated measures was used to assess for differences in PMP;W, oxygen uptake, heart rate (HR), minute ventilation, respiratory exchange ratio (RER) and subjective reports of local ratings of perceived exertion (LRPE) and central ratings of perceived exertion (CRPE), between three separate, but identical ACE tests. Participants were required to drink either 500 ml of a ‘sports performance’ drink (placebo), a ‘fatigue-inducing’ drink (nocebo) or water prior to exercise. The placebo caused a significant increase in PMP;W, and a significant decrease in LRPE compared to the nocebo (p=0.01; p=0.001) and water trials (p=0.01). No significant differences in PMP;W between the nocebo and water were found. However, the nocebo drink did cause a significant increase in LRPE (p=0.01). These results suggest that the time has come to broaden our understanding of the placebo and nocebo effects and their potential to impact sports performance.

The placebo and nocebo effects on peak minute power during incremental arm crank ergometry

This investigation aimed to explore the effects of inert sugar-free drinks described as either ‘performance enhancing’ (placebo) or ‘fatigue inducing’ (nocebo) on peak minute power (PMP;W) during incremental arm crank ergometry (ACE). Twelve healthy, non-specifically trained individuals volunteered to take part. A single-blind randomised controlled trial with repeated measures was used to assess for differences in PMP;W, oxygen uptake, heart rate (HR), minute ventilation, respiratory exchange ratio (RER) and subjective reports of local ratings of perceived exertion (LRPE) and central ratings of perceived exertion (CRPE), between three separate, but identical ACE tests. Participants were required to drink either 500 ml of a ‘sports performance’ drink (placebo), a ‘fatigue-inducing’ drink (nocebo) or water prior to exercise. The placebo caused a significant increase in PMP;W, and a significant decrease in LRPE compared to the nocebo (p=0.01; p=0.001) and water trials (p=0.01). No significant differences in PMP;W between the nocebo and water were found. However, the nocebo drink did cause a significant increase in LRPE (p=0.01). These results suggest that the time has come to broaden our understanding of the placebo and nocebo effects and their potential to impact sports performance.

The LH5 model for data mining

In the age of E-Business many companies faced with massive data sets that must be analysed for gaining a competitive edge. these data sets are in many instances incomplete and quite often not of very high quality. Although statistical analysis can be used to pre-process these data sets, this technique has its own limitations. In this paper we are presenting a system - and its underlying model - that can be used to test the integrity of existing data and pre-process the data into clearer data sets to be mined. LH5 is a rule-based system, capable of self-learning and is illustrated using a medical data set.

Gold, power, protest: Digital and social media and protests against large-scale mining projects in Colombia

Colombia’s Internet connectivity has increased immensely. Colombia has also ‘opened for business’, leading to an influx of extractive projects to which social movements object heavily. Studies on the role of digital media in political mobilisation in developing countries are still scarce. Using surveys, interviews, and reviews of literature, policy papers, website and social media content, this study examines the role of digital and social media in social movement organisations and asks how increased digital connectivity can help spread knowledge and mobilise mining protests. Results show that the use of new media in Colombia is hindered by socioeconomic constraints, fear of oppression, the constraints of keyboard activism and strong hierarchical power structures within social movements. Hence, effects on political mobilisation are still limited. Social media do not spontaneously produce non-hierarchical knowledge structures. Attention to both internal and external knowledge sharing is therefore conditional to optimising digital and social media use.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.