Energy consumption feedback in perspective: integrating Australian data to meta-analyses on in home displays

Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.

The MELODIES project: integrating diverse data using Linked Data and cloud computing

We present an overview of the MELODIES project, which is developing new data-intensive environmental services based on data from Earth Observation satellites, government databases, national and European agencies and more. We focus here on the capabilities and benefits of the project’s “technical platform”, which applies cloud computing and Linked Data technologies to enable the development of these services, providing flexibility and scalability.

A simple method for integrating a complex model into an ensemble data assimilation system using MPI

This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, {and gives the standards for implementing a data assimilation code to use such a model}. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) {functionality}. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to $2.7 \times 10^8$. The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques.

Preliminary ethnoarchaeological research on modern animal husbandry in Bestansur, Iraqi Kurdistan: integrating animal, plant and environmental data

This paper presents preliminary results from an ethnoarchaeological study of animal husbandry in the modern village of Bestansur, situated in the lower Zagros Mountains of Iraqi Kurdistan. This research explores how modern families use and manage their livestock within the local landscape and identifies traces of this use. The aim is to provide the groundwork for future archaeological investigations focusing on the nearby Neolithic site of Bestansur. This is based on the premise that modern behaviours can suggest testable patterns for past practices within the same functional and ecological domains. Semi-structured interviews conducted with villagers from several households provided large amounts of information on modern behaviours that helped direct data collection, and which also illustrate notable shifts in practices and use of the local landscape over time. Strontium isotope analysis of modern plant material demonstrates that a measurable variation exists between the alluvial floodplain and the lower foothills, while analysis of modern dung samples shows clear variation between sheep/goat and cow dung, in terms of numbers of faecal spherulites. These results are specific to the local environment of Bestansur and can be used for evaluating and contextualising archaeological evidence as well as providing modern reference material for comparative purposes.

The SUMA Project: Integrating Observational Data Assessment into Space and Service Design

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources

P>In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.

Historical biogeography and conservation of the golden-striped salamander (Chioglossa lusitanica) in northwestern Iberia: integrating ecological, phenotypic and phylogeographic data

The golden-striped salamander (Chioglossa lusitanica) is an endemic species inhabiting stream-side habitats in mountainous areas in the northwestern Iberian Peninsula. This salamandrid is listed in the IUCN Red Data Book as a threatened species. The combination of bioclimatic modeling of the species distribution and multivariate analysis of genetic and phenotypic data strengthens previous hypotheses concerning the historical biogeography of C. lusitanica: the Pleistocene subdivision of the species' range and a process of postglacial recolonization. Discrepancies between bioclimatic modeling predictions and the present-day distribution suggest that the species may still be expanding its range northwards. We propose the identification of two distinct units for the conservation of the species and suggest that this information should be taken into account in defining key areas for conservation in the Iberian Peninsula.

Petroleum contamination impact on macrobenthic communities under the influence of an oil refinery: Integrating chemical and biological multivariate data

Petroleum contamination impact on macrobenthic communities in the northeast portion of Todos os Santos Bay was assessed combining in multivariate analyses, chemical parameters such as aliphatic and polycyclic aromatic hydrocarbon indices and concentration ratios with benthic ecological parameters. Sediment samples were taken in August 2000 with a 0.05 m(2) van Veen grab at 28 sampling locations. The predominance of n-alkanes with more than 24 carbons, together with CPI values close to one, and the fact that most of the stations showed UCM/resolved aliphatic hydrocarbons ratios (UCM:R) higher than two, indicated a high degree of anthropogenic contribution, the presence of terrestrial plant detritus, petroleum products and evidence of chronic oil pollution. The indices used to determine the origin of PAH indicated the occurrence of a petrogenic contribution. A pyrolytic contribution constituted mainly by fossil fuel combustion derived PAH was also observed. The results of the stepwise multiple regression analysis performed with chemical data and benthic ecological descriptors demonstrated that not only total PAH concentrations but also specific concentration ratios or indices such as >= C24:< C24, An/178 and Fl/Fl + Py, are determining the structure of benthic communities within the study area. According to the BIO-ENV results petroleum related variables seemed to have a main influence on macrofauna community structure. The PCA ordination performed with the chemical data resulted in the formation of three groups of stations. The decrease in macrofauna density, number of species and diversity from groups III to I seemed to be related to the occurrence of high aliphatic hydrocarbon and PAH concentrations associated with fine sediments. Our results showed that macrobenthic communities in the northeast portion of Todos os Santos Bay are subjected to the impact of chronic oil pollution as was reflected by the reduction in the number of species and diversity. These results emphasise the importance to combine in multivariate approaches not only total hydrocarbon concentrations but also indices, isomer pair ratios and specific compound concentrations with biological data to improve the assessment of anthropogenic impact on marine ecosystems. (c) 2008 Elsevier Ltd. All rights reserved.

Service Descriptions and Linked Data for Integrating WSNs into Enterprise IT

This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Human Immunodeficiency Virus Reverse Transcriptase and Protease Sequence Database: an expanded data model integrating natural language text and sequence analysis programs

The HIV Reverse Transcriptase and Protease Sequence Database is an on-line relational database that catalogs evolutionary and drug-related sequence variation in the human immunodeficiency virus (HIV) reverse transcriptase (RT) and protease enzymes, the molecular targets of anti-HIV therapy (http://hivdb.stanford.edu). The database contains a compilation of nearly all published HIV RT and protease sequences, including submissions from International Collaboration databases and sequences published in journal articles. Sequences are linked to data about the source of the sequence sample and the antiretroviral drug treatment history of the individual from whom the isolate was obtained. During the past year 3500 sequences have been added and the data model has been expanded to include drug susceptibility data on sequenced isolates. Database content has also been integrated with didactic text and the output of two sequence analysis programs.

Integrating the development of data mining and data warehouses via model-driven engineering

Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.