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.

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

Combining data driven programming with component based software development:with applications in geovisualisation and dynamic data driven application systems

Software development methodologies are becoming increasingly abstract, progressing from low level assembly and implementation languages such as C and Ada, to component based approaches that can be used to assemble applications using technologies such as JavaBeans and the .NET framework. Meanwhile, model driven approaches emphasise the role of higher level models and notations, and embody a process of automatically deriving lower level representations and concrete software implementations. The relationship between data and software is also evolving. Modern data formats are becoming increasingly standardised, open and empowered in order to support a growing need to share data in both academia and industry. Many contemporary data formats, most notably those based on XML, are self-describing, able to specify valid data structure and content, and can also describe data manipulations and transformations. Furthermore, while applications of the past have made extensive use of data, the runtime behaviour of future applications may be driven by data, as demonstrated by the field of dynamic data driven application systems. The combination of empowered data formats and high level software development methodologies forms the basis of modern game development technologies, which drive software capabilities and runtime behaviour using empowered data formats describing game content. While low level libraries provide optimised runtime execution, content data is used to drive a wide variety of interactive and immersive experiences. This thesis describes the Fluid project, which combines component based software development and game development technologies in order to define novel component technologies for the description of data driven component based applications. The thesis makes explicit contributions to the fields of component based software development and visualisation of spatiotemporal scenes, and also describes potential implications for game development technologies. The thesis also proposes a number of developments in dynamic data driven application systems in order to further empower the role of data in this field.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

Architectural characterization of a delta-front reservoir analogue combining ground penetrating radar and electrical resistivity tomography: Roda Sandstone (Lower Eocene, Graus-Tremp basin, Spain)

Three-dimensional reconstruction of reservoir analogues can be improved combining data from different geophysical methods. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) data are valuable tools, since they provide subsurface information from internal architecture and facies distribution of sedimentary rock bodies, enabling the upgrading of depositional models and heterogeneity reconstruction. The Lower Eocene Roda Sandstone is a well-known deltaic complex widely studied as a reservoir analogue that displays a series of sandstone wedges with a general NE to SW progradational trend. To provide a better understanding of internal heterogeneity of a 10m-thick progradational delta-front sandstone unit, 3D GPR data were acquired. In addition, common midpoints (CMP) to measure the sandstone subsoil velocity, test profiles with different frequency antennas (25, 50 and 100MHz) and topographic data for subsequent correction in the geophysical data were also obtained. Three ERT profiles were also acquired to further constrain GPR analysis. These geophysical results illustrate the geometry of reservoir analogue heterogeneities both depositional and diagenetic in nature, improving and complementing previous outcrop-derived data. GPR interpretation using radar stratigraphy principles and attributes analysis provided: 1)tridimensional geometry of major stratigraphic surfaces that define four units in the GPR Prism, 2) image the internal architecture of the units and their statistical study of azimuth and dips, useful for a quick determination of paleocurrent directions. These results were used to define the depositional architecture of the progradational sandbody that shows an arrangement in very-high-frequency sequences characterized by clockwise paleocurrent variations and decrease of the sedimentary flow, similar to those observed at a greater scale in the same system. This high-frequency sequential arrangement has been attributed to the autocyclic dynamics of a supply-dominated delta- front where fluvial and tidal currents are in competition. The resistivity models enhanced the viewing of reservoir quality associated with cement distribution caused by depositional and early diagenetic processes related to the development of transgressive and regressive systems tracts in igh-frequency sequences.

Reconstruction of geomagnetic activity and near-Earth interplanetary conditions over the past 167 yr – Part 1: A new geomagnetic data composite

We present a new composite of geomagnetic activity which is designed to be as homogeneous in its construction as possible. This is done by only combining data that, by virtue of the locations of the source observatories used, have similar responses to solar wind and IMF (interplanetary magnetic field) variations. This will enable us (in Part 2, Lockwood et al., 2013a) to use the new index to reconstruct the interplanetary magnetic field, B, back to 1846 with a full analysis of errors. Allowance is made for the effects of secular change in the geomagnetic field. The composite uses interdiurnal variation data from Helsinki for 1845–1890 (inclusive) and 1893–1896 and from Eskdalemuir from 1911 to the present. The gaps are filled using data from the Potsdam (1891–1892 and 1897–1907) and the nearby Seddin observatories (1908–1910) and intercalibration achieved using the Potsdam–Seddin sequence. The new index is termed IDV(1d) because it employs many of the principles of the IDV index derived by Svalgaard and Cliver (2010), inspired by the u index of Bartels (1932); however, we revert to using one-day (1d) means, as employed by Bartels, because the use of near-midnight values in IDV introduces contamination by the substorm current wedge auroral electrojet, giving noise and a dependence on solar wind speed that varies with latitude. The composite is compared with independent, early data from European-sector stations, Greenwich, St Petersburg, Parc St Maur, and Ekaterinburg, as well as the composite u index, compiled from 2–6 stations by Bartels, and the IDV index of Svalgaard and Cliver. Agreement is found to be extremely good in all cases, except two. Firstly, the Greenwich data are shown to have gradually degraded in quality until new instrumentation was installed in 1915. Secondly, we infer that the Bartels u index is increasingly unreliable before about 1886 and overestimates the solar cycle amplitude between 1872 and 1883 and this is amplified in the proxy data used before 1872. This is therefore also true of the IDV index which makes direct use of the u index values.

Gridded bathymetry from multibeam echosounder EM122 data of the cruise M84/2, off Eregli (2011)

We investigated gas bubble emissions at the Don-Kuban paleo-fan in the northeastern Black Sea regarding their geological setting, quantities as well as spatial and temporal variabilities during three ship expeditions between 2007 and 2011. About 600 bubble-induced hydroacoustic anomalies in the water column (flares) originating from the seafloor above the gas hydrate stability zone (GHSZ) at ~700 m water depth were found. At about 890 m water depth a hydrocarbon seep area named "Kerch seep area" was newly discovered within the GHSZ. We propose locally domed sediments ('mounds') discovered during ultra-high resolution bathymetric mapping with an autonomous underwater vehicle (AUV) to result from gas hydrate accumulation at shallow depths. In situ measurements indicated spatially limited temperature elevations in the shallow sediment likely induced by upward fluid flow which may confine the local GHSZ to a few meters below the seafloor. As a result, gas bubbles are suspected to migrate into near-surface sediments and to escape the seafloor through small-scale faults. Hydroacoustic surveys revealed that several flares originated from a seafloor area of about 1 km**2 in size. The highest flare disappeared in about 350 m water depth, suggesting that the released methane remains in the water column. A methane flux estimate, combining data from visual quantifications during dives with a remotely operated vehicle (ROV) with results from ship-based hydroacoustic surveys and gas analysis revealed that between 2 and 87 x 10**6 mol CH4 yr-1 escaped into the water column above the Kerch seep area. Our results show that the finding of the Kerch seep area represents a so far underestimated type of hydrocarbon seep, which has to be considered in methane budget calculations.

Model evaluation and case series data

We discuss aggregation of data from neuropsychological patients and the process of evaluating models using data from a series of patients. We argue that aggregation can be misleading but not aggregating can also result in information loss. The basis for combining data needs to be theoretically defined, and the particular method of aggregation depends on the theoretical question and characteristics of the data. We present examples, often drawn from our own research, to illustrate these points. We also argue that statistical models and formal methods of model selection are a useful way to test theoretical accounts using data from several patients in multiple-case studies or case series. Statistical models can often measure fit in a way that explicitly captures what a theory allows; the parameter values that result from model fitting often measure theoretically important dimensions and can lead to more constrained theories or new predictions; and model selection allows the strength of evidence for models to be quantified without forcing this into the artificial binary choice that characterizes hypothesis testing methods. Methods that aggregate and then formally model patient data, however, are not automatically preferred to other methods. Which method is preferred depends on the question to be addressed, characteristics of the data, and practical issues like availability of suitable patients, but case series, multiple-case studies, single-case studies, statistical models, and process models should be complementary methods when guided by theory development.

Observations of QSO J2233-606 in the Southern Hubble Deep Field

The Hubble Deep Field South (HDF-S) Hubble Space Telescope (HST) observations are expected to begin in 1998 October. We present a composite spectrum of the QSO in the HDF-S held covering UV/optical/near-IR wavelengths, obtained by combining data from the Australian National University 2.3 m telescope with STIS on the HST.(1) This intermediate-resolution spectrum covers the range 1600-10000 Angstrom and allows us to derive some basic information on the intervening absorption systems which will be important in planning future higher resolution studies of this QSO. The QSO J2233 - 606 coordinates are alpha = 22(h)33(m)37(s).6, delta = -60 degrees 33'29 (J2000), the magnitude is B = 17.5, and its redshift is z(em) = 2.238, derived by simultaneously fitting several emission lines. The spectral index is alpha = -0.7 +/- 0.1, measured between the Ly alpha and Mg II emission lines. Many absorption systems are present, including systems with metal lines redward of the Ly alpha emission line at z(abs) 2.204, 1.942, 1.870, 1.787 and a few very strong Ly alpha features at z(abs) = 2.077, 1.928, without similarly strong metal lines. There is a conspicuous Lyman limit (LL) absorption system that is most likely associated with the z(abs) = 1.942 system with a neutral hydrogen column density of N-HI = (3.1 +/- 1.0) x 10(17) cm(-2). There is some evidence for the presence of a second LL absorber just to the blue of the conspicuous system at z = 1.870. We have employed a new technique, based on an analysis of the shape of the observed spectrum in the region of the LL absorption, to explore the properties of the gas. We tentatively conclude that this system might have suitable characteristics for measuring the deuterium-to-hydrogen (D/H) ratio.

Phylogenetic revision of Agapophytinae subf.n. (Diptera : Therevidae) based on molecular and morphological evidence

Agapophytinae subf.n. is a highly diverse lineage of Australasian Therevidae, comprising eight described and two new genera: Agapophytus Guerin-Meneville, Acupalpa Krober, Acraspisa Krober, Belonalys Krober, Bonjeania Irwin & Lyneborg, Parapsilocephala Krober, Acatopygia Krober, Laxotela Winterton & Irwin, Pipinnipons gen.n. and Patanothrix gen.n. A genus-level cladistic analysis of the subfamily was undertaken using sixty-eight adult morphological characters and c. 1000 base pairs of the elongation factor-1 alpha (EF-1 alpha) protein coding gene. The morphological data partition produced three most parsimonious cladograms, whereas the molecular data partition gave a single most parsimonious cladogram, which did not match any of the cladograms found in the morphological analysis. The level of congruence between the data partitions was determined using the partition homogeneity test (HTF) and Wilcoxon signed ranks rest. Despite being significantly incongruent in at least one of the incongruence tests, the partitions were combined in a simultaneous analysis. The combined data yielded a single cladogram that was better supported than that of the individual partitions analysed separately. The relative contributions of the data partitions to support for individual nodes on the combined cladogram were investigated using Partitioned Bremer Support. The level of support for many nodes on the combined cladogram was non-additive and often greater than the sum of support for the respective nodes on individual partitions. This synergistic interaction between incongruent data partitions indicates a common phylogenetic signal in both partitions. It also suggests that criteria for partition combination based solely on incongruence may be misleading. The phylogenetic relationships of the genera are discussed using the combined data. A key to genera of Agapophytinae is presented, with genera diagnosed and figured. Two new genera are described: Patanothrix with a new species (Pat. skevingtoni) and Pat. wilsoni (Mann) transferred from Parapsilocephala, and Pipinnipons with a new species (Pip. kroeberi). Pipinnipons fascipennis (Krober) is transferred from Squamopygin Krober and Pip. imitans (Mann) is transferred from Agapophytus. Agapophytus bicolor (Krober) is transferred from Parapsilocephala. Agapophytus varipennis Mann is synonymised with Aga, queenslandi Krober and Aga. flavicornis Mann is synonymised with Aga. pallidicornis (Krober).

How enterprise 2,0 firms take advantage of emergent social software platforms to manage knowledge

This research aims to provide a better understanding on how firms stimulate knowledge sharing through the utilization of collaboration tools, in particular Emergent Social Software Platforms (ESSPs). It focuses on the distinctive applications of ESSPs and on the initiatives contributing to maximize its advantages. In the first part of the research, I have itemized all types of existing collaboration tools and classify them in different categories according to their capabilities, objectives and according to their faculty for promoting knowledge sharing. In the second part, and based on an exploratory case study at Cisco Systems, I have identified the main applications of an existing enterprise social software platform named Webex Social. By combining a qualitative and quantitative approach, as well as combining data collected from survey’s results and from the analysis of the company’s documents, I am expecting to maximize the outcome of this investigation and reduce the risk of bias. Although effects cannot be universalized based on one single case study, some utilization patterns have been underlined from the data collected and potential trends in managing knowledge have been observed. The results of the research have also enabled identifying most of the constraints experienced by the users of the firm’s social software platform. Utterly, this research should provide a primary framework for firms planning to create or implement a social software platform and for firms willing to increase adoption levels and to promote the overall participation of users. It highlights the common traps that should be avoided by developers when designing a social software platform and the capabilities that it should inherently carry to support an effective knowledge management strategy.

Assessment of Physical Activity and Energy Expenditure by GPS Combined With Accelerometry in Real-Life Conditions.

Background: Physical activity (PA) and related energy expenditure (EE) is often assessed by means of a single technique. Because of inherent limitations, single techniques may not allow for an accurate assessment both PA and related EE. The aim of this study was to develop a model to accurately assess common PA types and durations and thus EE in free-living conditions, combining data from global positioning system (GPS) and 2 accelerometers. Methods: Forty-one volunteers participated in the study. First, a model was developed and adjusted to measured EE with a first group of subjects (Protocol I, n = 12) who performed 6 structured and supervised PA. Then, the model was validated over 2 experimental phases with 2 groups (n = 12 and n = 17) performing scheduled (Protocol I) and spontaneous common activities in real-life condition (Protocol II). Predicted EE was compared with actual EE as measured by portable indirect calorimetry. Results: In protocol I, performed PA types could be recognized with little error. The duration of each PA type could be predicted with an accuracy below 1 minute. Measured and predicted EE were strongly associated (r = .97, P < .001). Conclusion: Combining GPS and 2 accelerometers allows for an accurate assessment of PA and EE in free-living situations.

Nutrient patterns and their food sources in an International Study Setting: report from the EPIC study.

BACKGROUND Compared to food patterns, nutrient patterns have been rarely used particularly at international level. We studied, in the context of a multi-center study with heterogeneous data, the methodological challenges regarding pattern analyses. METHODOLOGY/PRINCIPAL FINDINGS We identified nutrient patterns from food frequency questionnaires (FFQ) in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study and used 24-hour dietary recall (24-HDR) data to validate and describe the nutrient patterns and their related food sources. Associations between lifestyle factors and the nutrient patterns were also examined. Principal component analysis (PCA) was applied on 23 nutrients derived from country-specific FFQ combining data from all EPIC centers (N = 477,312). Harmonized 24-HDRs available for a representative sample of the EPIC populations (N = 34,436) provided accurate mean group estimates of nutrients and foods by quintiles of pattern scores, presented graphically. An overall PCA combining all data captured a good proportion of the variance explained in each EPIC center. Four nutrient patterns were identified explaining 67% of the total variance: Principle component (PC) 1 was characterized by a high contribution of nutrients from plant food sources and a low contribution of nutrients from animal food sources; PC2 by a high contribution of micro-nutrients and proteins; PC3 was characterized by polyunsaturated fatty acids and vitamin D; PC4 was characterized by calcium, proteins, riboflavin, and phosphorus. The nutrients with high loadings on a particular pattern as derived from country-specific FFQ also showed high deviations in their mean EPIC intakes by quintiles of pattern scores when estimated from 24-HDR. Center and energy intake explained most of the variability in pattern scores. CONCLUSION/SIGNIFICANCE The use of 24-HDR enabled internal validation and facilitated the interpretation of the nutrient patterns derived from FFQs in term of food sources. These outcomes open research opportunities and perspectives of using nutrient patterns in future studies particularly at international level.

Improving blood pressure control through pharmacist interventions: a meta-analysis of randomized controlled trials.

BACKGROUND: Control of blood pressure (BP) remains a major challenge in primary care. Innovative interventions to improve BP control are therefore needed. By updating and combining data from 2 previous systematic reviews, we assess the effect of pharmacist interventions on BP and identify potential determinants of heterogeneity. METHODS AND RESULTS: Randomized controlled trials (RCTs) assessing the effect of pharmacist interventions on BP among outpatients with or without diabetes were identified from MEDLINE, EMBASE, CINAHL, and CENTRAL databases. Weighted mean differences in BP were estimated using random effect models. Prediction intervals (PI) were computed to better express uncertainties in the effect estimates. Thirty-nine RCTs were included with 14 224 patients. Pharmacist interventions mainly included patient education, feedback to physician, and medication management. Compared with usual care, pharmacist interventions showed greater reduction in systolic BP (-7.6 mm Hg, 95% CI: -9.0 to -6.3; I(2)=67%) and diastolic BP (-3.9 mm Hg, 95% CI: -5.1 to -2.8; I(2)=83%). The 95% PI ranged from -13.9 to -1.4 mm Hg for systolic BP and from -9.9 to +2.0 mm Hg for diastolic BP. The effect tended to be larger if the intervention was led by the pharmacist and was done at least monthly. CONCLUSIONS: Pharmacist interventions - alone or in collaboration with other healthcare professionals - improved BP management. Nevertheless, pharmacist interventions had differential effects on BP, from very large to modest or no effect; and determinants of heterogeneity could not be identified. Determining the most efficient, cost-effective, and least time-consuming intervention should be addressed with further research.

Is There a Crime Drop in Western Europe?

Combining data from police statistics and crime victim surveys, this article analyses the evolution of crime in Western Europe from 1988 to 2007. The results show that there is no general drop in crime. Property offences and homicide have been decreasing since the mid 1990s, while violent and drug offences have increased during the period under study. These trends highlight the limits of the explanations to the crime drop in the United States, which are based on the premise of a correlation in the evolution of all offences. The drop in property offences seems related to changes in the socioeconomic situation in Europe as well as to increases in security measures in households, and the reinforcement of private security. The increase in violent offences can be explained by the combination of several factors, including changes in youth's free time provoked by the development of the Internet, changing demographics, and the rise of episodic heavy alcohol consumption and street gangs.