WorldWideScience

Sample records for network temperature database

  1. Rett networked database

    DEFF Research Database (Denmark)

    Grillo, Elisa; Villard, Laurent; Clarke, Angus

    2012-01-01

    Rett syndrome (RTT) is a neurodevelopmental disorder with one principal phenotype and several distinct, atypical variants (Zappella, early seizure onset and congenital variants). Mutations in MECP2 are found in most cases of classic RTT but at least two additional genes, CDKL5 and FOXG1, can unde...... clinical features and mutations. We expect that the network will serve for the recruitment of patients into clinical trials and for developing quality measures to drive up standards of medical management....... underlie some (usually variant) cases. There is only limited correlation between genotype and phenotype. The Rett Networked Database (http://www.rettdatabasenetwork.org/) has been established to share clinical and genetic information. Through an "adaptor" process of data harmonization, a set of 293...... can expand indefinitely. Data are entered by a clinician in each center who supervises accuracy. This network was constructed to make available pooled international data for the study of RTT natural history and genotype-phenotype correlation and to indicate the proportion of patients with specific...

  2. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  3. The NASA Fireball Network Database

    Science.gov (United States)

    Moser, Danielle E.

    2011-01-01

    The NASA Meteoroid Environment Office (MEO) has been operating an automated video fireball network since late-2008. Since that time, over 1,700 multi-station fireballs have been observed. A database containing orbital data and trajectory information on all these events has recently been compiled and is currently being mined for information. Preliminary results are presented here.

  4. The ESID Online Database network.

    Science.gov (United States)

    Guzman, D; Veit, D; Knerr, V; Kindle, G; Gathmann, B; Eades-Perner, A M; Grimbacher, B

    2007-03-01

    Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform. The ESID Online Database is accessible via the official website (http://www.esid.org/). Supplementary data are available at Bioinformatics online.

  5. Nuclear technology databases and information network systems

    International Nuclear Information System (INIS)

    Iwata, Shuichi; Kikuchi, Yasuyuki; Minakuchi, Satoshi

    1993-01-01

    This paper describes the databases related to nuclear (science) technology, and information network. Following contents are collected in this paper: the database developed by JAERI, ENERGY NET, ATOM NET, NUCLEN nuclear information database, INIS, NUclear Code Information Service (NUCLIS), Social Application of Nuclear Technology Accumulation project (SANTA), Nuclear Information Database/Communication System (NICS), reactor materials database, radiation effects database, NucNet European nuclear information database, reactor dismantling database. (J.P.N.)

  6. The Global Terrestrial Network for Permafrost Database: metadata statistics and prospective analysis on future permafrost temperature and active layer depth monitoring site distribution

    Science.gov (United States)

    Biskaborn, B. K.; Lanckman, J.-P.; Lantuit, H.; Elger, K.; Streletskiy, D. A.; Cable, W. L.; Romanovsky, V. E.

    2015-03-01

    The Global Terrestrial Network for Permafrost (GTN-P) provides the first dynamic database associated with the Thermal State of Permafrost (TSP) and the Circumpolar Active Layer Monitoring (CALM) programs, which extensively collect permafrost temperature and active layer thickness data from Arctic, Antarctic and Mountain permafrost regions. The purpose of the database is to establish an "early warning system" for the consequences of climate change in permafrost regions and to provide standardized thermal permafrost data to global models. In this paper we perform statistical analysis of the GTN-P metadata aiming to identify the spatial gaps in the GTN-P site distribution in relation to climate-effective environmental parameters. We describe the concept and structure of the Data Management System in regard to user operability, data transfer and data policy. We outline data sources and data processing including quality control strategies. Assessment of the metadata and data quality reveals 63% metadata completeness at active layer sites and 50% metadata completeness for boreholes. Voronoi Tessellation Analysis on the spatial sample distribution of boreholes and active layer measurement sites quantifies the distribution inhomogeneity and provides potential locations of additional permafrost research sites to improve the representativeness of thermal monitoring across areas underlain by permafrost. The depth distribution of the boreholes reveals that 73% are shallower than 25 m and 27% are deeper, reaching a maximum of 1 km depth. Comparison of the GTN-P site distribution with permafrost zones, soil organic carbon contents and vegetation types exhibits different local to regional monitoring situations on maps. Preferential slope orientation at the sites most likely causes a bias in the temperature monitoring and should be taken into account when using the data for global models. The distribution of GTN-P sites within zones of projected temperature change show a high

  7. Temporal Databases in Network Management

    National Research Council Canada - National Science Library

    Gupta, Ajay

    1998-01-01

    .... This thesis discusses issues involved with performing network management, specifically with means of reducing and storing the large quantity of data that networks management tools and systems generate...

  8. The Danish Collaborative Bacteraemia Network (DACOBAN) database

    DEFF Research Database (Denmark)

    Gradel, Kim Oren; Schønheyder, Henrik Carl; Arpi, Magnus

    2014-01-01

    % of the Danish population). The database also includes data on comorbidity from the Danish National Patient Registry, vital status from the Danish Civil Registration System, and clinical data on 31% of nonselected records in the database. Use of the unique civil registration number given to all Danish residents......The Danish Collaborative Bacteraemia Network (DACOBAN) research database includes microbiological data obtained from positive blood cultures from a geographically and demographically well-defined population serviced by three clinical microbiology departments (1.7 million residents, 32...... enables linkage to additional registries for specific research projects. The DACOBAN database is continuously updated, and it currently comprises 39,292 patients with 49,951 bacteremic episodes from 2000 through 2011. The database is part of an international network of population-based bacteremia...

  9. Network and Database Security: Regulatory Compliance, Network, and Database Security - A Unified Process and Goal

    Directory of Open Access Journals (Sweden)

    Errol A. Blake

    2007-12-01

    Full Text Available Database security has evolved; data security professionals have developed numerous techniques and approaches to assure data confidentiality, integrity, and availability. This paper will show that the Traditional Database Security, which has focused primarily on creating user accounts and managing user privileges to database objects are not enough to protect data confidentiality, integrity, and availability. This paper is a compilation of different journals, articles and classroom discussions will focus on unifying the process of securing data or information whether it is in use, in storage or being transmitted. Promoting a change in Database Curriculum Development trends may also play a role in helping secure databases. This paper will take the approach that if one make a conscientious effort to unifying the Database Security process, which includes Database Management System (DBMS selection process, following regulatory compliances, analyzing and learning from the mistakes of others, Implementing Networking Security Technologies, and Securing the Database, may prevent database breach.

  10. Wisconsin Inventors` Network Database final report

    Energy Technology Data Exchange (ETDEWEB)

    1991-12-04

    The Wisconsin Innovation Service Center at UW-Whitewater received a DOE grant to create an Inventor`s Network Database to assist independent inventors and entrepreneurs with new product development. Since 1980, the Wisconsin Innovation Service Center (WISC) at the University of Wisconsin-Whitewater has assisted independent and small business inventors in estimating the marketability of their new product ideas and inventions. The purpose of the WISC as an economic development entity is to encourage inventors who appear to have commercially viable inventions, based on preliminary market research, to invest in the next stages of development, perhaps investigating prototype development, legal protection, or more in-depth market research. To address inventor`s information needs, WISC developed on electronic database with search capabilities by geographic region and by product category/industry. It targets both public and private resources capable of, and interested in, working with individual and small business inventors. At present, the project includes resources in Wisconsin only.

  11. A Bayesian Network Schema for Lessening Database Inference

    National Research Council Canada - National Science Library

    Chang, LiWu; Moskowitz, Ira S

    2001-01-01

    .... The authors introduce a formal schema for database inference analysis, based upon a Bayesian network structure, which identifies critical parameters involved in the inference problem and represents...

  12. Wireless Sensor Networks Database: Data Management and Implementation

    Directory of Open Access Journals (Sweden)

    Ping Liu

    2014-04-01

    Full Text Available As the core application of wireless sensor network technology, Data management and processing have become the research hotspot in the new database. This article studied mainly data management in wireless sensor networks, in connection with the characteristics of the data in wireless sensor networks, discussed wireless sensor network data query, integrating technology in-depth, proposed a mobile database structure based on wireless sensor network and carried out overall design and implementation for the data management system. In order to achieve the communication rules of above routing trees, network manager uses a simple maintenance algorithm of routing trees. Design ordinary node end, server end in mobile database at gathering nodes and mobile client end that can implement the system, focus on designing query manager, storage modules and synchronous module at server end in mobile database at gathering nodes.

  13. The Network Configuration of an Object Relational Database Management System

    Science.gov (United States)

    Diaz, Philip; Harris, W. C.

    2000-01-01

    The networking and implementation of the Oracle Database Management System (ODBMS) requires developers to have knowledge of the UNIX operating system as well as all the features of the Oracle Server. The server is an object relational database management system (DBMS). By using distributed processing, processes are split up between the database server and client application programs. The DBMS handles all the responsibilities of the server. The workstations running the database application concentrate on the interpretation and display of data.

  14. Schefferville Permafrost Temperature Database, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of ground temperature data from 192 boreholes in the area of Schefferville, Quebec (54°48'N, 66°50'W), located within the discontinuous...

  15. Database Software Selection for the Egyptian National STI Network.

    Science.gov (United States)

    Slamecka, Vladimir

    The evaluation and selection of information/data management system software for the Egyptian National Scientific and Technical (STI) Network are described. An overview of the state-of-the-art of database technology elaborates on the differences between information retrieval and database management systems (DBMS). The desirable characteristics of…

  16. Insertion algorithms for network model database management systems

    Science.gov (United States)

    Mamadolimov, Abdurashid; Khikmat, Saburov

    2017-12-01

    The network model is a database model conceived as a flexible way of representing objects and their relationships. Its distinguishing feature is that the schema, viewed as a graph in which object types are nodes and relationship types are arcs, forms partial order. When a database is large and a query comparison is expensive then the efficiency requirement of managing algorithms is minimizing the number of query comparisons. We consider updating operation for network model database management systems. We develop a new sequantial algorithm for updating operation. Also we suggest a distributed version of the algorithm.

  17. Network and Database Security: Regulatory Compliance, Network, and Database Security - A Unified Process and Goal

    OpenAIRE

    Errol A. Blake

    2007-01-01

    Database security has evolved; data security professionals have developed numerous techniques and approaches to assure data confidentiality, integrity, and availability. This paper will show that the Traditional Database Security, which has focused primarily on creating user accounts and managing user privileges to database objects are not enough to protect data confidentiality, integrity, and availability. This paper is a compilation of different journals, articles and classroom discussions ...

  18. SoyFN: a knowledge database of soybean functional networks.

    Science.gov (United States)

    Xu, Yungang; Guo, Maozu; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

    2014-01-01

    Many databases for soybean genomic analysis have been built and made publicly available, but few of them contain knowledge specifically targeting the omics-level gene-gene, gene-microRNA (miRNA) and miRNA-miRNA interactions. Here, we present SoyFN, a knowledge database of soybean functional gene networks and miRNA functional networks. SoyFN provides user-friendly interfaces to retrieve, visualize, analyze and download the functional networks of soybean genes and miRNAs. In addition, it incorporates much information about KEGG pathways, gene ontology annotations and 3'-UTR sequences as well as many useful tools including SoySearch, ID mapping, Genome Browser, eFP Browser and promoter motif scan. SoyFN is a schema-free database that can be accessed as a Web service from any modern programming language using a simple Hypertext Transfer Protocol call. The Web site is implemented in Java, JavaScript, PHP, HTML and Apache, with all major browsers supported. We anticipate that this database will be useful for members of research communities both in soybean experimental science and bioinformatics. Database URL: http://nclab.hit.edu.cn/SoyFN.

  19. ODIN. Online Database Information Network: ODIN Policy & Procedure Manual.

    Science.gov (United States)

    Townley, Charles T.; And Others

    Policies and procedures are outlined for the Online Database Information Network (ODIN), a cooperative of libraries in south-central Pennsylvania, which was organized to improve library services through technology. The first section covers organization and goals, members, and responsibilities of the administrative council and libraries. Patrons…

  20. A distributed database view of network tracking systems

    Science.gov (United States)

    Yosinski, Jason; Paffenroth, Randy

    2008-04-01

    In distributed tracking systems, multiple non-collocated trackers cooperate to fuse local sensor data into a global track picture. Generating this global track picture at a central location is fairly straightforward, but the single point of failure and excessive bandwidth requirements introduced by centralized processing motivate the development of decentralized methods. In many decentralized tracking systems, trackers communicate with their peers via a lossy, bandwidth-limited network in which dropped, delayed, and out of order packets are typical. Oftentimes the decentralized tracking problem is viewed as a local tracking problem with a networking twist; we believe this view can underestimate the network complexities to be overcome. Indeed, a subsequent 'oversight' layer is often introduced to detect and handle track inconsistencies arising from a lack of robustness to network conditions. We instead pose the decentralized tracking problem as a distributed database problem, enabling us to draw inspiration from the vast extant literature on distributed databases. Using the two-phase commit algorithm, a well known technique for resolving transactions across a lossy network, we describe several ways in which one may build a distributed multiple hypothesis tracking system from the ground up to be robust to typical network intricacies. We pay particular attention to the dissimilar challenges presented by network track initiation vs. maintenance and suggest a hybrid system that balances speed and robustness by utilizing two-phase commit for only track initiation transactions. Finally, we present simulation results contrasting the performance of such a system with that of more traditional decentralized tracking implementations.

  1. Development of high temperature property database for Alloy 800H

    International Nuclear Information System (INIS)

    Yokoyama, Norio; Watanabe, Katsutoshi; Tsuji, Hirokazu; Nakajima, Hajime.

    1993-07-01

    JAERI Material Performance Database (JMPD) has been developed since 1989 in JAERI with a view to utilizing the various kinds of characteristic data of nuclear materials efficiently. Using relational database management system, PLANNER on the mainframe, the JMPD provides the retrieval supporting system, graphic and statistical analyses system. The data obtained with 7868 sets on characteristic data of metallic materials including fatigue crack growth data, etc. have been stored in the JMPD at the end of March in 1993. A ferritic superalloy, Alloy 800H is used for the structural material of the control rods of the High Temperature Engineering Test Reactor (HTTR). Thermal stress generates which might cause a severe creep damage at a reactor scram. It therefore needs to be designed with consideration on the fracture modes induced by creep deformation after neutron irradiation. The creep data (approximately 240 sets) and tensile data (approximately 100 sets) of Alloy 800H including the effects of test environment, aging treatment and neutron irradiation have been stored in the JMPD. Furthermore, using a personal computer, high temperature property database for Alloy 800H has been developed. The present report outlines the development of high temperature property database for Alloy 800H. (author)

  2. Extracting reaction networks from databases-opening Pandora's box.

    Science.gov (United States)

    Fearnley, Liam G; Davis, Melissa J; Ragan, Mark A; Nielsen, Lars K

    2014-11-01

    Large quantities of information describing the mechanisms of biological pathways continue to be collected in publicly available databases. At the same time, experiments have increased in scale, and biologists increasingly use pathways defined in online databases to interpret the results of experiments and generate hypotheses. Emerging computational techniques that exploit the rich biological information captured in reaction systems require formal standardized descriptions of pathways to extract these reaction networks and avoid the alternative: time-consuming and largely manual literature-based network reconstruction. Here, we systematically evaluate the effects of commonly used knowledge representations on the seemingly simple task of extracting a reaction network describing signal transduction from a pathway database. We show that this process is in fact surprisingly difficult, and the pathway representations adopted by various knowledge bases have dramatic consequences for reaction network extraction, connectivity, capture of pathway crosstalk and in the modelling of cell-cell interactions. Researchers constructing computational models built from automatically extracted reaction networks must therefore consider the issues we outline in this review to maximize the value of existing pathway knowledge. © The Author 2013. Published by Oxford University Press.

  3. Distributed Database Semantic Integration of Wireless Sensor Network to Access the Environmental Monitoring System

    Directory of Open Access Journals (Sweden)

    Ubaidillah Umar

    2018-06-01

    Full Text Available A wireless sensor network (WSN works continuously to gather information from sensors that generate large volumes of data to be handled and processed by applications. Current efforts in sensor networks focus more on networking and development services for a variety of applications and less on processing and integrating data from heterogeneous sensors. There is an increased need for information to become shareable across different sensors, database platforms, and applications that are not easily implemented in traditional database systems. To solve the issue of these large amounts of data from different servers and database platforms (including sensor data, a semantic sensor web service platform is needed to enable a machine to extract meaningful information from the sensor’s raw data. This additionally helps to minimize and simplify data processing and to deduce new information from existing data. This paper implements a semantic web data platform (SWDP to manage the distribution of data sensors based on the semantic database system. SWDP uses sensors for temperature, humidity, carbon monoxide, carbon dioxide, luminosity, and noise. The system uses the Sesame semantic web database for data processing and a WSN to distribute, minimize, and simplify information processing. The sensor nodes are distributed in different places to collect sensor data. The SWDP generates context information in the form of a resource description framework. The experiment results demonstrate that the SWDP is more efficient than the traditional database system in terms of memory usage and processing time.

  4. Handling of network and database instabilities in CORAL

    International Nuclear Information System (INIS)

    Trentadue, R; Valassi, A; Kalkhof, A

    2012-01-01

    The CORAL software is widely used by the LHC experiments for storing and accessing data using relational database technologies. CORAL provides a C++ abstraction layer that supports data persistency for several back-ends and deployment models, direct client access to Oracle servers being one of the most important use cases. Since 2010, several problems have been reported by the LHC experiments in their use of Oracle through CORAL, involving application errors, hangs or crashes after the network or the database servers became temporarily unavailable. CORAL already provided some level of handling of these instabilities, which are due to external causes and cannot be avoided, but this proved to be insufficient in some cases and to be itself the cause of other problems, such as the hangs and crashes mentioned before, in other cases. As a consequence, a major redesign of the CORAL plugins has been implemented, with the aim of making the software more robust against these database and network glitches. The new implementation ensures that CORAL automatically reconnects to Oracle databases in a transparent way whenever possible and gently terminates the application when this is not possible. Internally, this is done by resetting all relevant parameters of the underlying back-end technology (OCI, the Oracle Call Interface). This presentation reports on the status of this work at the time of the CHEP2012 conference, covering the design and implementation of these new features and the outlook for future developments in this area.

  5. The River Network of Montenegro in the GIS Database

    Directory of Open Access Journals (Sweden)

    Goran Barović

    2017-06-01

    Full Text Available The subject of this paper is the systematization and precise identification of the structure of river networks in Montenegro in both planimetric and hypsometric dimensions, using cartometry. This includes the precise determination of the morphometric parameters of river flows, their numerical display, graphical display, and documentation. This allows for a number of analyses, for example, of individual catchments, the mutual relations of individual watercourses within a higher order catchment, and the classification of flows according to river and sea basins and their relationship to the environment. In addition, there is the potential for expanding the database further, with a view to continuous, systematic, scientific and practical follow-up in all or part of the geographic space. The cartometric analysis of the river network in Montenegro has a special scientific, and also a social value. In the geographical structure of all countries, including Montenegro, rivers occupy a central place as individual elements and integral parts of the whole. There is almost no human activity which is not related to river flows, or related phenomena and processes. The river network as part of a geographic space continues to gain in importance, and therefore studying it must connect with the other structural elements within which it functions. These are the basic relief characteristics, climate, and certain hydrographic characteristics. A complete theoretical and methodological approach to this problem forms the basis for a scientific understanding of the significance of the river network of Montenegro.

  6. Research on Construction of Road Network Database Based on Video Retrieval Technology

    Directory of Open Access Journals (Sweden)

    Wang Fengling

    2017-01-01

    Full Text Available Based on the characteristics of the video database and the basic structure of the video database and several typical video data models, the segmentation-based multi-level data model is used to describe the landscape information video database, the network database model and the road network management database system. Landscape information management system detailed design and implementation of a detailed preparation.

  7. The European Narcolepsy Network (EU-NN) database

    DEFF Research Database (Denmark)

    Khatami, Ramin; Luca, Gianina; Baumann, Christian R

    2016-01-01

    Narcolepsy with cataplexy is a rare disease with an estimated prevalence of 0.02% in European populations. Narcolepsy shares many features of rare disorders, in particular the lack of awareness of the disease with serious consequences for healthcare supply. Similar to other rare diseases, only a ......, identification of post-marketing medication side-effects, and will contribute to improve clinical trial designs and provide facilities to further develop phase III trials....... Narcolepsy Network is introduced. The database structure, standardization of data acquisition and quality control procedures are described, and an overview provided of the first 1079 patients from 18 European specialized centres. Due to its standardization this continuously increasing data pool is most...

  8. Wisconsin Inventors' Network Database final report

    Energy Technology Data Exchange (ETDEWEB)

    1991-12-04

    The Wisconsin Innovation Service Center at UW-Whitewater received a DOE grant to create an Inventor's Network Database to assist independent inventors and entrepreneurs with new product development. Since 1980, the Wisconsin Innovation Service Center (WISC) at the University of Wisconsin-Whitewater has assisted independent and small business inventors in estimating the marketability of their new product ideas and inventions. The purpose of the WISC as an economic development entity is to encourage inventors who appear to have commercially viable inventions, based on preliminary market research, to invest in the next stages of development, perhaps investigating prototype development, legal protection, or more in-depth market research. To address inventor's information needs, WISC developed on electronic database with search capabilities by geographic region and by product category/industry. It targets both public and private resources capable of, and interested in, working with individual and small business inventors. At present, the project includes resources in Wisconsin only.

  9. East-China Geochemistry Database (ECGD):A New Networking Database for North China Craton

    Science.gov (United States)

    Wang, X.; Ma, W.

    2010-12-01

    North China Craton is one of the best natural laboratories that research some Earth Dynamic questions[1]. Scientists made much progress in research on this area, and got vast geochemistry data, which are essential for answering many fundamental questions about the age, composition, structure, and evolution of the East China area. But the geochemical data have long been accessible only through the scientific literature and theses where they have been widely dispersed, making it difficult for the broad Geosciences community to find, access and efficiently use the full range of available data[2]. How to effectively store, manage, share and reuse the existing geochemical data in the North China Craton area? East-China Geochemistry Database(ECGD) is a networking geochemical scientific database system that has been designed based on WebGIS and relational database for the structured storage and retrieval of geochemical data and geological map information. It is integrated the functions of data retrieval, spatial visualization and online analysis. ECGD focus on three areas: 1.Storage and retrieval of geochemical data and geological map information. Research on the characters of geochemical data, including its composing and connecting of each other, we designed a relational database, which based on geochemical relational data model, to store a variety of geological sample information such as sampling locality, age, sample characteristics, reference, major elements, rare earth elements, trace elements and isotope system et al. And a web-based user-friendly interface is provided for constructing queries. 2.Data view. ECGD is committed to online data visualization by different ways, especially to view data in digital map with dynamic way. Because ECGD was integrated WebGIS technology, the query results can be mapped on digital map, which can be zoomed, translation and dot selection. Besides of view and output query results data by html, txt or xls formats, researchers also can

  10. Neural networks to predict exosphere temperature corrections

    Science.gov (United States)

    Choury, Anna; Bruinsma, Sean; Schaeffer, Philippe

    2013-10-01

    Precise orbit prediction requires a forecast of the atmospheric drag force with a high degree of accuracy. Artificial neural networks are universal approximators derived from artificial intelligence and are widely used for prediction. This paper presents a method of artificial neural networking for prediction of the thermosphere density by forecasting exospheric temperature, which will be used by the semiempirical thermosphere Drag Temperature Model (DTM) currently developed. Artificial neural network has shown to be an effective and robust forecasting model for temperature prediction. The proposed model can be used for any mission from which temperature can be deduced accurately, i.e., it does not require specific training. Although the primary goal of the study was to create a model for 1 day ahead forecast, the proposed architecture has been generalized to 2 and 3 days prediction as well. The impact of artificial neural network predictions has been quantified for the low-orbiting satellite Gravity Field and Steady-State Ocean Circulation Explorer in 2011, and an order of magnitude smaller orbit errors were found when compared with orbits propagated using the thermosphere model DTM2009.

  11. PL/SQL and Bind Variable: the two ways to increase the efficiency of Network Databases

    Directory of Open Access Journals (Sweden)

    Hitesh KUMAR SHARMA

    2011-12-01

    Full Text Available Modern data analysis applications are driven by the Network databases. They are pushing traditional database and data warehousing technologies beyond their limits due to their massively increasing data volumes and demands for low latency. There are three major challenges in working with network databases: interoperability due to heterogeneous data repositories, proactively due to autonomy of data sources and high efficiency to meet the application demand. This paper provides the two ways to meet the third challenge of network databases. This goal can be achieved by network database administrator with the usage of PL/SQL blocks and bind variable. The paper will explain the effect of PL/SQL block and bind variable on Network database efficiency to meet the modern data analysis application demand.

  12. Prediction of Austenite Formation Temperatures Using Artificial Neural Networks

    International Nuclear Information System (INIS)

    Schulze, P; Schmidl, E; Grund, T; Lampke, T

    2016-01-01

    For the modeling and design of heat treatments, in consideration of the development/ transformation of the microstructure, different material data depending on the chemical composition, the respective microstructure/phases and the temperature are necessary. Material data are, e.g. the thermal conductivity, heat capacity, thermal expansion and transformation data etc. The quality of thermal simulations strongly depends on the accuracy of the material data. For many materials, the required data - in particular for different microstructures and temperatures - are rare in the literature. In addition, a different chemical composition within the permitted limits of the considered steel alloy cannot be predicted. A solution for this problem is provided by the calculation of material data using Artificial Neural Networks (ANN). In the present study, the start and finish temperatures of the transformation from the bcc lattice to the fcc lattice structure of hypoeutectoid steels are calculated using an Artificial Neural Network. An appropriate database containing different transformation temperatures (austenite formation temperatures) to train the ANN is selected from the literature. In order to find a suitable feedforward network, the network topologies as well as the activation functions of the hidden layers are varied and subsequently evaluated in terms of the prediction accuracy. The transformation temperatures calculated by the ANN exhibit a very good compliance compared to the experimental data. The results show that the prediction performance is even higher compared to classical empirical equations such as Andrews or Brandis. Therefore, it can be assumed that the presented ANN is a convenient tool to distinguish between bcc and fcc phases in hypoeutectoid steels. (paper)

  13. Prediction of Austenite Formation Temperatures Using Artificial Neural Networks

    Science.gov (United States)

    Schulze, P.; Schmidl, E.; Grund, T.; Lampke, T.

    2016-03-01

    For the modeling and design of heat treatments, in consideration of the development/ transformation of the microstructure, different material data depending on the chemical composition, the respective microstructure/phases and the temperature are necessary. Material data are, e.g. the thermal conductivity, heat capacity, thermal expansion and transformation data etc. The quality of thermal simulations strongly depends on the accuracy of the material data. For many materials, the required data - in particular for different microstructures and temperatures - are rare in the literature. In addition, a different chemical composition within the permitted limits of the considered steel alloy cannot be predicted. A solution for this problem is provided by the calculation of material data using Artificial Neural Networks (ANN). In the present study, the start and finish temperatures of the transformation from the bcc lattice to the fcc lattice structure of hypoeutectoid steels are calculated using an Artificial Neural Network. An appropriate database containing different transformation temperatures (austenite formation temperatures) to train the ANN is selected from the literature. In order to find a suitable feedforward network, the network topologies as well as the activation functions of the hidden layers are varied and subsequently evaluated in terms of the prediction accuracy. The transformation temperatures calculated by the ANN exhibit a very good compliance compared to the experimental data. The results show that the prediction performance is even higher compared to classical empirical equations such as Andrews or Brandis. Therefore, it can be assumed that the presented ANN is a convenient tool to distinguish between bcc and fcc phases in hypoeutectoid steels.

  14. A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network

    Science.gov (United States)

    Lussana, C.; Ranci, M.; Uboldi, F.

    2012-04-01

    In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.

  15. Databases

    Digital Repository Service at National Institute of Oceanography (India)

    Kunte, P.D.

    Information on bibliographic as well as numeric/textual databases relevant to coastal geomorphology has been included in a tabular form. Databases cover a broad spectrum of related subjects like coastal environment and population aspects, coastline...

  16. A Database Design and Development Case: NanoTEK Networks

    Science.gov (United States)

    Ballenger, Robert M.

    2010-01-01

    This case provides a real-world project-oriented case study for students enrolled in a management information systems, database management, or systems analysis and design course in which database design and development are taught. The case consists of a business scenario to provide background information and details of the unique operating…

  17. Databases

    Directory of Open Access Journals (Sweden)

    Nick Ryan

    2004-01-01

    Full Text Available Databases are deeply embedded in archaeology, underpinning and supporting many aspects of the subject. However, as well as providing a means for storing, retrieving and modifying data, databases themselves must be a result of a detailed analysis and design process. This article looks at this process, and shows how the characteristics of data models affect the process of database design and implementation. The impact of the Internet on the development of databases is examined, and the article concludes with a discussion of a range of issues associated with the recording and management of archaeological data.

  18. SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

    Science.gov (United States)

    Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A

    2018-01-01

    Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this

  19. The research of network database security technology based on web service

    Science.gov (United States)

    Meng, Fanxing; Wen, Xiumei; Gao, Liting; Pang, Hui; Wang, Qinglin

    2013-03-01

    Database technology is one of the most widely applied computer technologies, its security is becoming more and more important. This paper introduced the database security, network database security level, studies the security technology of the network database, analyzes emphatically sub-key encryption algorithm, applies this algorithm into the campus-one-card system successfully. The realization process of the encryption algorithm is discussed, this method is widely used as reference in many fields, particularly in management information system security and e-commerce.

  20. Curvature and temperature of complex networks.

    Science.gov (United States)

    Krioukov, Dmitri; Papadopoulos, Fragkiskos; Vahdat, Amin; Boguñá, Marián

    2009-09-01

    We show that heterogeneous degree distributions in observed scale-free topologies of complex networks can emerge as a consequence of the exponential expansion of hidden hyperbolic space. Fermi-Dirac statistics provides a physical interpretation of hyperbolic distances as energies of links. The hidden space curvature affects the heterogeneity of the degree distribution, while clustering is a function of temperature. We embed the internet into the hyperbolic plane and find a remarkable congruency between the embedding and our hyperbolic model. Besides proving our model realistic, this embedding may be used for routing with only local information, which holds significant promise for improving the performance of internet routing.

  1. Pacific Ocean buoy temperature date - TAO/TRITON database & National Buoy Data Center database

    Data.gov (United States)

    U.S. Environmental Protection Agency — Pacific Ocean buoy temperature data. This dataset is associated with the following publication: Carbone, F., M. Landis, C.N. Gencarelli, A. Naccarato, F. Sprovieri,...

  2. Development of temperature related thermal neutron scattering database for MCNP

    International Nuclear Information System (INIS)

    Mei Longwei; Cai Xiangzhou; Jiang Dazhen; Chen Jingen; Guo Wei

    2013-01-01

    Based on ENDF/B-Ⅶ neutron library, the thermal neutron scattering library S(α, β) for molten salt reactor moderators was developed. The temperatures of this library were chose as the characteristic temperature of the molten salt reactor. The cross section of the thermal neutron scattering of ACE format was investigated, and this library was also validated by the benchmarks of ICSBEP. The uncertainties shown in the validation were in reasonable range when compared with the thermal neutron scattering library tmccs which included in the MCNP data library. It was proved that the thermal neutron scattering library processed in this study could be used in the molten salt reactor design. (authors)

  3. A central database for the Global Terrestrial Network for Permafrost (GTN-P)

    Science.gov (United States)

    Elger, Kirsten; Lanckman, Jean-Pierre; Lantuit, Hugues; Karlsson, Ævar Karl; Johannsson, Halldór

    2013-04-01

    The Global Terrestrial Network for Permafrost (GTN-P) is the primary international observing network for permafrost sponsored by the Global Climate Observing System (GCOS) and the Global Terrestrial Observing System (GTOS), and managed by the International Permafrost Association (IPA). It monitors the Essential Climate Variable (ECV) permafrost that consists of permafrost temperature and active-layer thickness, with the long-term goal of obtaining a comprehensive view of the spatial structure, trends, and variability of changes in the active layer and permafrost. The network's two international monitoring components are (1) CALM (Circumpolar Active Layer Monitoring) and the (2) Thermal State of Permafrost (TSP), which is made of an extensive borehole-network covering all permafrost regions. Both programs have been thoroughly overhauled during the International Polar Year 2007-2008 and extended their coverage to provide a true circumpolar network stretching over both Hemispheres. GTN-P has gained considerable visibility in the science community in providing the baseline against which models are globally validated and incorporated in climate assessments. Yet it was until now operated on a voluntary basis, and is now being redesigned to meet the increasing expectations from the science community. To update the network's objectives and deliver the best possible products to the community, the IPA organized a workshop to define the user's needs and requirements for the production, archival, storage and dissemination of the permafrost data products it manages. From the beginning on, GNT-P data was "outfitted" with an open data policy with free data access via the World Wide Web. The existing data, however, is far from being homogeneous: is not yet optimized for databases, there is no framework for data reporting or archival and data documentation is incomplete. As a result, and despite the utmost relevance of permafrost in the Earth's climate system, the data has not been

  4. Fish Karyome: A karyological information network database of Indian Fishes.

    Science.gov (United States)

    Nagpure, Naresh Sahebrao; Pathak, Ajey Kumar; Pati, Rameshwar; Singh, Shri Prakash; Singh, Mahender; Sarkar, Uttam Kumar; Kushwaha, Basdeo; Kumar, Ravindra

    2012-01-01

    'Fish Karyome', a database on karyological information of Indian fishes have been developed that serves as central source for karyotype data about Indian fishes compiled from the published literature. Fish Karyome has been intended to serve as a liaison tool for the researchers and contains karyological information about 171 out of 2438 finfish species reported in India and is publically available via World Wide Web. The database provides information on chromosome number, morphology, sex chromosomes, karyotype formula and cytogenetic markers etc. Additionally, it also provides the phenotypic information that includes species name, its classification, and locality of sample collection, common name, local name, sex, geographical distribution, and IUCN Red list status. Besides, fish and karyotype images, references for 171 finfish species have been included in the database. Fish Karyome has been developed using SQL Server 2008, a relational database management system, Microsoft's ASP.NET-2008 and Macromedia's FLASH Technology under Windows 7 operating environment. The system also enables users to input new information and images into the database, search and view the information and images of interest using various search options. Fish Karyome has wide range of applications in species characterization and identification, sex determination, chromosomal mapping, karyo-evolution and systematics of fishes.

  5. A meta-database comparison from various European Research and Monitoring Networks dedicated to forest sites

    Czech Academy of Sciences Publication Activity Database

    Danielewska, A.; Clarke, N.; Olejnik, Janusz; Hansen, K.; de Vries, W.; Lundin, L.; Tuovinen, J-P.; Fischer, R.; Urbaniak, M.; Paoletti, E.

    2013-01-01

    Roč. 6, JAN 2013 (2013), s. 1-9 ISSN 1971-7458 Institutional support: RVO:67179843 Keywords : Research and Monitoring Network * Meta- database * Forest * Monitoring Subject RIV: EH - Ecology, Behaviour Impact factor: 1.150, year: 2013

  6. Research on Big Data Attribute Selection Method in Submarine Optical Fiber Network Fault Diagnosis Database

    Directory of Open Access Journals (Sweden)

    Chen Ganlang

    2017-11-01

    Full Text Available At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper, a large data attribute selection method based on support vector machines (SVM for fault diagnosis database of submarine optical fiber network is proposed. Mining large data in the database of optical fiber network fault diagnosis, and calculate its attribute weight, attribute classification is completed according to attribute weight, so as to complete attribute selection of large data. Experimental results prove that ,the proposed method can improve the accuracy of large data attribute selection in fault diagnosis database of submarine optical fiber network, and has high use value.

  7. CMRegNet-An interspecies reference database for corynebacterial and mycobacterial regulatory networks

    DEFF Research Database (Denmark)

    Abreu, Vinicius A C; Almeida, Sintia; Tiwari, Sandeep

    2015-01-01

    gene regulatory network can lead to various practical applications, creating a greater understanding of how organisms control their cellular behavior. DESCRIPTION: In this work, we present a new database, CMRegNet for the gene regulatory networks of Corynebacterium glutamicum ATCC 13032......Net to date the most comprehensive database of regulatory interactions of CMNR bacteria. The content of CMRegNet is publicly available online via a web interface found at http://lgcm.icb.ufmg.br/cmregnet ....

  8. The shortest path algorithm performance comparison in graph and relational database on a transportation network

    Directory of Open Access Journals (Sweden)

    Mario Miler

    2014-02-01

    Full Text Available In the field of geoinformation and transportation science, the shortest path is calculated on graph data mostly found in road and transportation networks. This data is often stored in various database systems. Many applications dealing with transportation network require calculation of the shortest path. The objective of this research is to compare the performance of Dijkstra shortest path calculation in PostgreSQL (with pgRouting and Neo4j graph database for the purpose of determining if there is any difference regarding the speed of the calculation. Benchmarking was done on commodity hardware using OpenStreetMap road network. The first assumption is that Neo4j graph database would be well suited for the shortest path calculation on transportation networks but this does not come without some cost. Memory proved to be an issue in Neo4j setup when dealing with larger transportation networks.

  9. 24-Hour Forecast of Air Temperatures from the National Weather Service's National Digital Forecast Database (NDFD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Digital Forecast Database (NDFD) contains a seamless mosaic of the National Weather Service's (NWS) digital forecasts of air temperature. In...

  10. 72-Hour Forecast of Air Temperatures from the National Weather Service's National Digital Forecast Database (NDFD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Digital Forecast Database (NDFD) contains a seamless mosaic of the National Weather Service's (NWS) digital forecasts of air temperature. In...

  11. 48-Hour Forecast of Air Temperatures from the National Weather Service's National Digital Forecast Database (NDFD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Digital Forecast Database (NDFD) contains a seamless mosaic of the National Weather Service's (NWS) digital forecasts of air temperature. In...

  12. Location in Mobile Networks Using Database Correlation (DCM

    Directory of Open Access Journals (Sweden)

    Michal Mada

    2008-01-01

    Full Text Available The article presents one of the methods of location (DCM, which is suitable for using in urban environments, where other methods are less accurate. The principle of this method is in comparison of measured samples of signal with samples stored in database. Next the article deals with methods for processing the data and other possibilities of correction of location.

  13. Computer application for database management and networking of service radio physics

    International Nuclear Information System (INIS)

    Ferrando Sanchez, A.; Cabello Murillo, E.; Diaz Fuentes, R.; Castro Novais, J.; Clemente Gutierrez, F.; Casa de Juan, M. A. de la; Adaimi Hernandez, P.

    2011-01-01

    The databases in the quality control prove to be a powerful tool for recording, management and statistical process control. Developed in a Windows environment and under Access (Micros of Office) our service implements this philosophy on the canter's computer network. A computer that acts as the server provides the database to the treatment units to record quality control measures daily and incidents. To remove shortcuts stop working with data migration, possible use of duplicate and erroneous data loss because of errors in network connections, which are common problems, we proceeded to manage connections and access to databases ease of maintenance and use horn to all service personnel.

  14. Multiple k Nearest Neighbor Query Processing in Spatial Network Databases

    DEFF Research Database (Denmark)

    Xuegang, Huang; Jensen, Christian Søndergaard; Saltenis, Simonas

    2006-01-01

    This paper concerns the efficient processing of multiple k nearest neighbor queries in a road-network setting. The assumed setting covers a range of scenarios such as the one where a large population of mobile service users that are constrained to a road network issue nearest-neighbor queries...... for points of interest that are accessible via the road network. Given multiple k nearest neighbor queries, the paper proposes progressive techniques that selectively cache query results in main memory and subsequently reuse these for query processing. The paper initially proposes techniques for the case...... where an upper bound on k is known a priori and then extends the techniques to the case where this is not so. Based on empirical studies with real-world data, the paper offers insight into the circumstances under which the different proposed techniques can be used with advantage for multiple k nearest...

  15. Content-based organization of the information space in multi-database networks

    NARCIS (Netherlands)

    Papazoglou, M.; Milliner, S.

    1998-01-01

    Abstract. Rapid growth in the volume of network-available data, complexity, diversity and terminological fluctuations, at different data sources, render network-accessible information increasingly difficult to achieve. The situation is particularly cumbersome for users of multi-database systems who

  16. Analyzing GAIAN Database (GaianDB) on a Tactical Network

    Science.gov (United States)

    2015-11-30

    databases, and other files, and exposes them as 1 unified structured query language ( SQL )-compliant data source. This “store locally query anywhere...UDP server that could communicate directly with the CSRs via the CSR’s serial port. However, GAIAN has over 800,000 lines of source code. It...management, by which all would have to be modified to communicate with our server and maintain utility. Not only did we quickly realize that this

  17. Fluid temperatures: Modeling the thermal regime of a river network

    Science.gov (United States)

    Rhonda Mazza; Ashley Steel

    2017-01-01

    Water temperature drives the complex food web of a river network. Aquatic organisms hatch, feed, and reproduce in thermal niches within the tributaries and mainstem that comprise the river network. Changes in water temperature can synchronize or asynchronize the timing of their life stages throughout the year. The water temperature fluctuates over time and place,...

  18. Trajectory Based Optimal Segment Computation in Road Network Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    2013-01-01

    Finding a location for a new facility such that the facility attracts the maximal number of customers is a challenging problem. Existing studies either model customers as static sites and thus do not consider customer movement, or they focus on theoretical aspects and do not provide solutions...... that are shown empirically to be scalable. Given a road network, a set of existing facilities, and a collection of customer route traversals, an optimal segment query returns the optimal road network segment(s) for a new facility. We propose a practical framework for computing this query, where each route...... traversal is assigned a score that is distributed among the road segments covered by the route according to a score distribution model. The query returns the road segment(s) with the highest score. To achieve low latency, it is essential to prune the very large search space. We propose two algorithms...

  19. Trajectory Based Optimal Segment Computation in Road Network Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    Finding a location for a new facility such that the facility attracts the maximal number of customers is a challenging problem. Existing studies either model customers as static sites and thus do not consider customer movement, or they focus on theoretical aspects and do not provide solutions...... that are shown empirically to be scalable. Given a road network, a set of existing facilities, and a collection of customer route traversals, an optimal segment query returns the optimal road network segment(s) for a new facility. We propose a practical framework for computing this query, where each route...... traversal is assigned a score that is distributed among the road segments covered by the route according to a score distribution model. The query returns the road segment(s) with the highest score. To achieve low latency, it is essential to prune the very large search space. We propose two algorithms...

  20. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

    Science.gov (United States)

    Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

    2015-01-01

    With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

  1. Flexible network reconstruction from relational databases with Cytoscape and CytoSQL.

    Science.gov (United States)

    Laukens, Kris; Hollunder, Jens; Dang, Thanh Hai; De Jaeger, Geert; Kuiper, Martin; Witters, Erwin; Verschoren, Alain; Van Leemput, Koenraad

    2010-07-01

    Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be imported in Cytoscape in various file formats, or directly from external databases through specialized third party plugins. However, molecular data are often stored in relational databases with their own specific structure, for which dedicated plugins do not exist. Therefore, a more generic solution is presented. A new Cytoscape plugin 'CytoSQL' is developed to connect Cytoscape to any relational database. It allows to launch SQL ('Structured Query Language') queries from within Cytoscape, with the option to inject node or edge features of an existing network as SQL arguments, and to convert the retrieved data to Cytoscape network components. Supported by a set of case studies we demonstrate the flexibility and the power of the CytoSQL plugin in converting specific data subsets into meaningful network representations. CytoSQL offers a unified approach to let Cytoscape interact with relational databases. Thanks to the power of the SQL syntax, this tool can rapidly generate and enrich networks according to very complex criteria. The plugin is available at http://www.ptools.ua.ac.be/CytoSQL.

  2. Development of a neoclassical transport database by neural network fitting in LHD

    International Nuclear Information System (INIS)

    Wakasa, Arimitsu; Oikawa, Shun-ichi; Murakami, Sadayoshi; Yamada, Hiroshi; Yokoyama, Masayuki; Watanabe, Kiyomasa; Maassberg, Hening; Beidler, Craig D.

    2004-01-01

    A database of neoclassical transport coefficients for the Large Helical Device is developed using normalized mono-energetic diffusion coefficients evaluated by Monte Carlo simulation code; DCOM. A neural network fitting method is applied to take energy convolutions with the given distribution function, e.g. Maxwellian. The database gives the diffusion coefficients as a function of the collision frequency, the radial electric field and the minor radius position. (author)

  3. Data Linkage Graph: computation, querying and knowledge discovery of life science database networks

    Directory of Open Access Journals (Sweden)

    Lange Matthias

    2007-12-01

    Full Text Available To support the interpretation of measured molecular facts, like gene expression experiments or EST sequencing, the functional or the system biological context has to be considered. Doing so, the relationship to existing biological knowledge has to be discovered. In general, biological knowledge is worldwide represented in a network of databases. In this paper we present a method for knowledge extraction in life science databases, which prevents the scientists from screen scraping and web clicking approaches.

  4. New model for distributed multimedia databases and its application to networking of museums

    Science.gov (United States)

    Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

    1998-02-01

    This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

  5. An online database for informing ecological network models: http://kelpforest.ucsc.edu.

    Science.gov (United States)

    Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

    2014-01-01

    Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

  6. The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database.

    Science.gov (United States)

    Hall, Richard J; Murray, Christopher W; Verdonk, Marcel L

    2017-07-27

    The hit validation stage of a fragment-based drug discovery campaign involves probing the SAR around one or more fragment hits. This often requires a search for similar compounds in a corporate collection or from commercial suppliers. The Fragment Network is a graph database that allows a user to efficiently search chemical space around a compound of interest. The result set is chemically intuitive, naturally grouped by substitution pattern and meaningfully sorted according to the number of observations of each transformation in medicinal chemistry databases. This paper describes the algorithms used to construct and search the Fragment Network and provides examples of how it may be used in a drug discovery context.

  7. Design of special purpose database for credit cooperation bank business processing network system

    Science.gov (United States)

    Yu, Yongling; Zong, Sisheng; Shi, Jinfa

    2011-12-01

    With the popularization of e-finance in the city, the construction of e-finance is transfering to the vast rural market, and quickly to develop in depth. Developing the business processing network system suitable for the rural credit cooperative Banks can make business processing conveniently, and have a good application prospect. In this paper, We analyse the necessity of adopting special purpose distributed database in Credit Cooperation Band System, give corresponding distributed database system structure , design the specical purpose database and interface technology . The application in Tongbai Rural Credit Cooperatives has shown that system has better performance and higher efficiency.

  8. Databases as policy instruments. About extending networks as evidence-based policy

    Directory of Open Access Journals (Sweden)

    Stoevelaar Herman

    2007-12-01

    Full Text Available Abstract Background This article seeks to identify the role of databases in health policy. Access to information and communication technologies has changed traditional relationships between the state and professionals, creating new systems of surveillance and control. As a result, databases may have a profound effect on controlling clinical practice. Methods We conducted three case studies to reconstruct the development and use of databases as policy instruments. Each database was intended to be employed to control the use of one particular pharmaceutical in the Netherlands (growth hormone, antiretroviral drugs for HIV and Taxol, respectively. We studied the archives of the Dutch Health Insurance Board, conducted in-depth interviews with key informants and organized two focus groups, all focused on the use of databases both in policy circles and in clinical practice. Results Our results demonstrate that policy makers hardly used the databases, neither for cost control nor for quality assurance. Further analysis revealed that these databases facilitated self-regulation and quality assurance by (national bodies of professionals, resulting in restrictive prescription behavior amongst physicians. Conclusion The databases fulfill control functions that were formerly located within the policy realm. The databases facilitate collaboration between policy makers and physicians, since they enable quality assurance by professionals. Delegating regulatory authority downwards into a network of physicians who control the use of pharmaceuticals seems to be a good alternative for centralized control on the basis of monitoring data.

  9. Experience and Lessons learnt from running High Availability Databases on Network Attached Storage

    CERN Document Server

    Guijarro, Manuel

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department supplies the Oracle Central Database services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been setup. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS (Network File System) as shared disk space for RAC purposes and Data hosting. It is composed of two private LANs (Local Area Network), one to provide access to the NAS filers and a second to implement the Oracle RAC private interconnect, both using Network Bonding. NAS filers are configured in partnership to prevent having single points of failure and to provide automatic NAS filer fail-over.

  10. Experience and lessons learnt from running high availability databases on network attached storage

    International Nuclear Information System (INIS)

    Guijarro, M; Gaspar, R

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department supplies the Oracle Central Database services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been setup. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS (Network File System) as shared disk space for RAC purposes and Data hosting. It is composed of two private LANs (Local Area Network), one to provide access to the NAS filers and a second to implement the Oracle RAC private interconnect, both using Network Bonding. NAS filers are configured in partnership to prevent having single points of failure and to provide automatic NAS filer fail-over

  11. Moving to Google Cloud: Renovation of Global Borehole Temperature Database for Climate Research

    Science.gov (United States)

    Xiong, Y.; Huang, S.

    2013-12-01

    Borehole temperature comprises an independent archive of information on climate change which is complementary to the instrumental and other proxy climate records. With support from the international geothermal community, a global database of borehole temperatures has been constructed for the specific purpose of the study on climate change. Although this database has become an important data source in climate research, there are certain limitations partially because the framework of the existing borehole temperature database was hand-coded some twenty years ago. A database renovation work is now underway to take the advantages of the contemporary online database technologies. The major intended improvements include 1) dynamically linking a borehole site to Google Earth to allow for inspection of site specific geographical information; 2) dynamically linking an original key reference of a given borehole site to Google Scholar to allow for a complete list of related publications; and 3) enabling site selection and data download based on country, coordinate range, and contributor. There appears to be a good match between the enhancement requirements for this database and the functionalities of the newly released Google Fusion Tables application. Google Fusion Tables is a cloud-based service for data management, integration, and visualization. This experimental application can consolidate related online resources such as Google Earth, Google Scholar, and Google Drive for sharing and enriching an online database. It is user friendly, allowing users to apply filters and to further explore the internet for additional information regarding the selected data. The users also have ways to map, to chart, and to calculate on the selected data, and to download just the subset needed. The figure below is a snapshot of the database currently under Google Fusion Tables renovation. We invite contribution and feedback from the geothermal and climate research community to make the

  12. A Bayesian network approach to the database search problem in criminal proceedings

    Science.gov (United States)

    2012-01-01

    Background The ‘database search problem’, that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions

  13. Exergy and Energy Analysis of Low Temperature District Heating Network

    DEFF Research Database (Denmark)

    Li, Hongwei; Svendsen, Svend

    is in line with a pilot project that is carrying out in Denmark with network supply/return temperature at 55oC/25 oC. The consumer domestic hot water (DHW) demand is supplied with a special designed district heating (DH) storage tank. The space heating (SH) demand is supplied with a low temperature radiator......Low temperature district heating (LTDH) with reduced network supply and return temperature provides better match of the low quality building thermal demand and the low quality waste heat supply. In this paper, an exemplary LTDH network was designed for 30 low energy demand residential houses, which....... The network thermal and hydraulic conditions were simulated under steady state with an in-house district heating network design and simulation code. Through simulation, the overall system energetic and exergetic efficiencies were calculated and the exergy losses for the major district heating system...

  14. A Database of Tornado Events as Perceived by the USArray Transportable Array Network

    Science.gov (United States)

    Tytell, J. E.; Vernon, F.; Reyes, J. C.

    2015-12-01

    Over the course of the deployment of Earthscope's USArray Transportable Array (TA) network there have numerous tornado events that have occurred within the changing footprint of its network. The Array Network Facility based in San Diego, California, has compiled a database of these tornado events based on data provided by the NOAA Storm Prediction Center (SPC). The SPC data itself consists of parameters such as start-end point track data for each event, maximum EF intensities, and maximum track widths. Our database is Antelope driven and combines these data from the SPC with detailed station information from the TA network. We are now able to list all available TA stations during any specific tornado event date and also provide a single calculated "nearest" TA station per individual tornado event. We aim to provide this database as a starting resource for those with an interest in investigating tornado signatures within surface pressure and seismic response data. On a larger scale, the database may be of particular interest to the infrasound research community

  15. STITCH 2: an interaction network database for small molecules and proteins

    DEFF Research Database (Denmark)

    Kuhn, Michael; Szklarczyk, Damian; Franceschini, Andrea

    2010-01-01

    Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug......-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other...... chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/....

  16. Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

    Science.gov (United States)

    Miryala, Sravan Kumar; Anbarasu, Anand; Ramaiah, Sudha

    2018-02-05

    Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Baumbach Jan

    2007-11-01

    Full Text Available Abstract Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user can be analyzed in the context of known

  18. Energy and exergy analysis of low temperature district heating network

    International Nuclear Information System (INIS)

    Li, Hongwei; Svendsen, Svend

    2012-01-01

    Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply. -- Highlights: ► Exergy and energy analysis for low and medium temperature district heating systems. ► Different district heating network dimensioning methods are analyzed. ► Major exergy losses are identified in the district heating network and the in-house substations. ► Advantages to apply low temperature district heating are highlighted through exergy analysis. ► The influence of thermal by-pass on system exergy/energy performance is analyzed.

  19. Network-based statistical comparison of citation topology of bibliographic databases

    Science.gov (United States)

    Šubelj, Lovro; Fiala, Dalibor; Bajec, Marko

    2014-01-01

    Modern bibliographic databases provide the basis for scientific research and its evaluation. While their content and structure differ substantially, there exist only informal notions on their reliability. Here we compare the topological consistency of citation networks extracted from six popular bibliographic databases including Web of Science, CiteSeer and arXiv.org. The networks are assessed through a rich set of local and global graph statistics. We first reveal statistically significant inconsistencies between some of the databases with respect to individual statistics. For example, the introduced field bow-tie decomposition of DBLP Computer Science Bibliography substantially differs from the rest due to the coverage of the database, while the citation information within arXiv.org is the most exhaustive. Finally, we compare the databases over multiple graph statistics using the critical difference diagram. The citation topology of DBLP Computer Science Bibliography is the least consistent with the rest, while, not surprisingly, Web of Science is significantly more reliable from the perspective of consistency. This work can serve either as a reference for scholars in bibliometrics and scientometrics or a scientific evaluation guideline for governments and research agencies. PMID:25263231

  20. A global multiproxy database for temperature reconstructions of the Common Era

    Science.gov (United States)

    Emile-Geay, Julian; McKay, Nicholas P.; Kaufman, Darrell S.; von Gunten, Lucien; Wang, Jianghao; Anchukaitis, Kevin J.; Abram, Nerilie J.; Addison, Jason A.; Curran, Mark A.J.; Evans, Michael N.; Henley, Benjamin J.; Hao, Zhixin; Martrat, Belen; McGregor, Helen V.; Neukom, Raphael; Pederson, Gregory T.; Stenni, Barbara; Thirumalai, Kaustubh; Werner, Johannes P.; Xu, Chenxi; Divine, Dmitry V.; Dixon, Bronwyn C.; Gergis, Joelle; Mundo, Ignacio A.; Nakatsuka, T.; Phipps, Steven J.; Routson, Cody C.; Steig, Eric J.; Tierney, Jessica E.; Tyler, Jonathan J.; Allen, Kathryn J.; Bertler, Nancy A. N.; Bjorklund, Jesper; Chase, Brian M.; Chen, Min-Te; Cook, Ed; de Jong, Rixt; DeLong, Kristine L.; Dixon, Daniel A.; Ekaykin, Alexey A.; Ersek, Vasile; Filipsson, Helena L.; Francus, Pierre; Freund, Mandy B.; Frezzotti, M.; Gaire, Narayan P.; Gajewski, Konrad; Ge, Quansheng; Goosse, Hugues; Gornostaeva, Anastasia; Grosjean, Martin; Horiuchi, Kazuho; Hormes, Anne; Husum, Katrine; Isaksson, Elisabeth; Kandasamy, Selvaraj; Kawamura, Kenji; Koc, Nalan; Leduc, Guillaume; Linderholm, Hans W.; Lorrey, Andrew M.; Mikhalenko, Vladimir; Mortyn, P. Graham; Motoyama, Hideaki; Moy, Andrew D.; Mulvaney, Robert; Munz, Philipp M.; Nash, David J.; Oerter, Hans; Opel, Thomas; Orsi, Anais J.; Ovchinnikov, Dmitriy V.; Porter, Trevor J.; Roop, Heidi; Saenger, Casey; Sano, Masaki; Sauchyn, David; Saunders, K.M.; Seidenkrantz, Marit-Solveig; Severi, Mirko; Shao, X.; Sicre, Marie-Alexandrine; Sigl, Michael; Sinclair, Kate; St. George, Scott; St. Jacques, Jeannine-Marie; Thamban, Meloth; Thapa, Udya Kuwar; Thomas, E.; Turney, Chris; Uemura, Ryu; Viau, A.E.; Vladimirova, Diana O.; Wahl, Eugene; White, James W. C.; Yu, Z.; Zinke, Jens

    2017-01-01

    Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

  1. LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

    Directory of Open Access Journals (Sweden)

    Priyanka Patel

    2016-03-01

    Full Text Available A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level. Keywords: L.major, S.mansoni, Regulatory networks, Transcription factors, Database

  2. An XML-Based Networking Method for Connecting Distributed Anthropometric Databases

    Directory of Open Access Journals (Sweden)

    H Cheng

    2007-03-01

    Full Text Available Anthropometric data are used by numerous types of organizations for health evaluation, ergonomics, apparel sizing, fitness training, and many other applications. Data have been collected and stored in electronic databases since at least the 1940s. These databases are owned by many organizations around the world. In addition, the anthropometric studies stored in these databases often employ different standards, terminology, procedures, or measurement sets. To promote the use and sharing of these databases, the World Engineering Anthropometry Resources (WEAR group was formed and tasked with the integration and publishing of member resources. It is easy to see that organizing worldwide anthropometric data into a single database architecture could be a daunting and expensive undertaking. The challenges of WEAR integration reflect mainly in the areas of distributed and disparate data, different standards and formats, independent memberships, and limited development resources. Fortunately, XML schema and web services provide an alternative method for networking databases, referred to as the Loosely Coupled WEAR Integration. A standard XML schema can be defined and used as a type of Rosetta stone to translate the anthropometric data into a universal format, and a web services system can be set up to link the databases to one another. In this way, the originators of the data can keep their data locally along with their own data management system and user interface, but their data can be searched and accessed as part of the larger data network, and even combined with the data of others. This paper will identify requirements for WEAR integration, review XML as the universal format, review different integration approaches, and propose a hybrid web services/data mart solution.

  3. The Coral Reef Temperature Anomaly Database (CoRTAD) - Global, 4 km, Sea Surface Temperature and Related Thermal Stress Metrics for 1985-2005 (NODC Accession 0044419)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  4. Long-Term Collaboration Network Based on ClinicalTrials.gov Database in the Pharmaceutical Industry

    Directory of Open Access Journals (Sweden)

    Heyoung Yang

    2018-01-01

    Full Text Available Increasing costs, risks, and productivity problems in the pharmaceutical industry are important recent issues in the biomedical field. Open innovation is proposed as a solution to these issues. However, little statistical analysis related to collaboration in the pharmaceutical industry has been conducted so far. Meanwhile, not many cases have analyzed the clinical trials database, even though it is the information source with the widest coverage for the pharmaceutical industry. The purpose of this study is to test the clinical trials information as a probe for observing the status of the collaboration network and open innovation in the pharmaceutical industry. This study applied the social network analysis method to clinical trials data from 1980 to 2016 in ClinicalTrials.gov. Data were divided into four time periods—1980s, 1990s, 2000s, and 2010s—and the collaboration network was constructed for each time period. The characteristic of each network was investigated. The types of agencies participating in the clinical trials were classified as a university, national institute, company, or other, and the major players in the collaboration networks were identified. This study showed some phenomena related to the pharmaceutical industry that could provide clues to policymakers about open innovation. If follow-up studies were conducted, the utilization of the clinical trial database could be further expanded, which is expected to help open innovation in the pharmaceutical industry.

  5. Database for nuclear-waste disposal for temperatures up to 3000C

    International Nuclear Information System (INIS)

    Phillips, S.L.; Silvester, L.F.

    1982-09-01

    A computerized database is compiled of evaluated thermodynamic data for aqueous species associated with nuclear waste storage. The data are organized as hydrolysis and formation constants; solubilities of oxides and hydroxides; and, as Nernstian potentials. More emphasis is on stability constants. Coeffficients are given to calculate stability constants at various ionic strengths and to high temperatures. Results are presented as tables for selected species including uranium, amorphous silica and actinides

  6. Smooth Information Flow in Temperature Climate Network Reflects Mass Transport

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Jajcay, Nikola; Hartman, David; Paluš, Milan

    2017-01-01

    Roč. 27, č. 3 (2017), č. článku 035811. ISSN 1054-1500 R&D Projects: GA ČR GCP103/11/J068; GA MŠk LH14001 Institutional support: RVO:67985807 Keywords : directed network * causal network * Granger causality * climate network * information flow * temperature network Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.283, year: 2016

  7. Evaluation of thermal network correction program using test temperature data

    Science.gov (United States)

    Ishimoto, T.; Fink, L. C.

    1972-01-01

    An evaluation process to determine the accuracy of a computer program for thermal network correction is discussed. The evaluation is required since factors such as inaccuracies of temperatures, insufficient number of temperature points over a specified time period, lack of one-to-one correlation between temperature sensor and nodal locations, and incomplete temperature measurements are not present in the computer-generated information. The mathematical models used in the evaluation are those that describe a physical system composed of both a conventional and a heat pipe platform. A description of the models used, the results of the evaluation of the thermal network correction, and input instructions for the thermal network correction program are presented.

  8. Application of Wireless Sensor Networks for Indoor Temperature Regulation

    DEFF Research Database (Denmark)

    Stojkoska, Biljana Risteska; Popovska Avramova, Andrijana; Chatzimisios, Periklis

    2014-01-01

    Wireless sensor networks take a major part in our everyday lives by enhancing systems for home automation, healthcare, temperature control, energy consumption monitoring, and so forth. In this paper we focus on a system used for temperature regulation for residential, educational, industrial...... energy savings by reducing the amount of data transmissions through the network. Furthermore, the framework explores techniques for localization, such that the location of the nodes can be used by algorithms that regulate temperature settings......., and commercial premises, and so forth. We propose a framework for indoor temperature regulation and optimization using wireless sensor networks based on ZigBee platform. This paper considers architectural design of the system, as well as implementation guidelines. The proposed system favors methods that provide...

  9. Energy and exergy analysis of low temperature district heating network

    DEFF Research Database (Denmark)

    Li, Hongwei; Svendsen, Svend

    2012-01-01

    is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand...... energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply.......Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network...

  10. ISOE: an international occupational exposure database and communications network for dose optimisation

    International Nuclear Information System (INIS)

    Robinson, I.F.; Lazo, E.

    1995-01-01

    The Information System on Occupational Exposure (ISOE) was launched by the Nuclear Energy Agency (NEA) of the Organisation for Economic Co-operation and Development (OECD) on 1 January 1992 to facilitate the communication of dosimetry and ALARA implementation data among nuclear facilities around the world. Members of ISOE include 51 utilities from 17 countries and regulators from 11 countries, with four regional technical centres administering the system and a Steering Group which manages the work. ISOE includes three databases and a communications network at several levels. The three databases NEA1, NEA2 and NEA3 include varying levels of details, with NEA3 being the most detailed giving task and site specific ALARA practices and experiences. Utility membership of ISOE gives full access to the databases whereas regulators have more limited access. This paper reviews the current status of participation, describes the three databases and the communications network. Some dose data showing trends in particular countries are presented as well as dose data relating to operation cycle length and outage length. The advantages of membership are described, and it is concluded that ISOE holds the potential for both dose and cost savings. (author)

  11. PharmDB-K: Integrated Bio-Pharmacological Network Database for Traditional Korean Medicine.

    Directory of Open Access Journals (Sweden)

    Ji-Hyun Lee

    Full Text Available Despite the growing attention given to Traditional Medicine (TM worldwide, there is no well-known, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-associated drugs (compound, disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software and BioMart (a data federation framework for convenient search and analysis of the TKM network. Database URL: http://pharmdb-k.org, http://biomart.i-pharm.org.

  12. Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2007-10-01

    Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

  13. Construction and evaluation of yeast expression networks by database-guided predictions

    Directory of Open Access Journals (Sweden)

    Katharina Papsdorf

    2016-05-01

    Full Text Available DNA-Microarrays are powerful tools to obtain expression data on the genome-wide scale. We performed microarray experiments to elucidate the transcriptional networks, which are up- or down-regulated in response to the expression of toxic polyglutamine proteins in yeast. Such experiments initially generate hit lists containing differentially expressed genes. To look into transcriptional responses, we constructed networks from these genes. We therefore developed an algorithm, which is capable of dealing with very small numbers of microarrays by clustering the hits based on co-regulatory relationships obtained from the SPELL database. Here, we evaluate this algorithm according to several criteria and further develop its statistical capabilities. Initially, we define how the number of SPELL-derived co-regulated genes and the number of input hits influences the quality of the networks. We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. We find that this approach is useful for our own experimental data sets and also for many other data sets which we tested from the SPELL microarray database. Furthermore, the clusters obtained by the described algorithm greatly improve the assignment to biological processes and transcription factors for the individual clusters. Thus, the described clustering approach, which will be available through the ClusterEx web interface, and the evaluation parameters derived from it represent valuable tools for the fast and informative analysis of yeast microarray data.

  14. Wireless Sensor Networks Framework for Indoor Temperature Regulation

    DEFF Research Database (Denmark)

    Stojkoska, Biljana; Popovska Avramova, Andrijana

    2013-01-01

    Wireless Sensor Networks take a major part in our everyday lives by enhancing systems for home automation, health-care, temperature control, energy consumption monitoring etc. In this paper we focus on a system used for temperature regulation for homes, educational, industrial, commercial premises...... etc. We propose a framework for indoor regulation and optimization of temperature using wireless sensor networks based on ZigBee. Methods for optimal temperature regulation are suggested and discussed. The framework is based on methods that provide energy savings by reducing the amount of data...... transmissions through prediction methods. Additionally the framework explores techniques for localization, such that the location of the nodes is used for optimization of the temperature settings. Information on node location is used to provide the most optimal tradeo between the time it takes to reach...

  15. Citation buidelines for nuclear data retrieved from databases resident at the Nuclear Data Centers Network

    International Nuclear Information System (INIS)

    McLane, V.

    1996-07-01

    The Nuclear Data Centers Network is a world-wide cooperation of nuclear data centers under the auspices of the International Atomic Energy Agency. The Network organizes the task of collecting, compiling, standardizing, storing, assessing, and distributing the nuclear data on an international scale. Information available at the Centers includes bibliographic, experimental, and evaluated databases for nuclear reaction data and for nuclear structure and radioactive decay data. The objective of the Network is to provide the information to users in a convenient, readily-available form. To this end, online data services have been established at three of the centers: the National Nuclear Data Center (NNDC), the Nuclear Data Section of the International Atomic Energy Agency (NDS), and the OECD Nuclear Energy Agency Data Bank (NEADB). Some information is also available at the NNDC and NEADB World Wide Web sites

  16. Application of new type of distributed multimedia databases to networked electronic museum

    Science.gov (United States)

    Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

    1999-01-01

    Recently, various kinds of multimedia application systems have actively been developed based on the achievement of advanced high sped communication networks, computer processing technologies, and digital contents-handling technologies. Under this background, this paper proposed a new distributed multimedia database system which can effectively perform a new function of cooperative retrieval among distributed databases. The proposed system introduces a new concept of 'Retrieval manager' which functions as an intelligent controller so that the user can recognize a set of distributed databases as one logical database. The logical database dynamically generates and performs a preferred combination of retrieving parameters on the basis of both directory data and the system environment. Moreover, a concept of 'domain' is defined in the system as a managing unit of retrieval. The retrieval can effectively be performed by cooperation of processing among multiple domains. Communication language and protocols are also defined in the system. These are used in every action for communications in the system. A language interpreter in each machine translates a communication language into an internal language used in each machine. Using the language interpreter, internal processing, such internal modules as DBMS and user interface modules can freely be selected. A concept of 'content-set' is also introduced. A content-set is defined as a package of contents. Contents in the content-set are related to each other. The system handles a content-set as one object. The user terminal can effectively control the displaying of retrieved contents, referring to data indicating the relation of the contents in the content- set. In order to verify the function of the proposed system, a networked electronic museum was experimentally built. The results of this experiment indicate that the proposed system can effectively retrieve the objective contents under the control to a number of distributed

  17. United States Historical Climatology Network Daily Temperature and Precipitation Data (1871-1997)

    Energy Technology Data Exchange (ETDEWEB)

    Easterling, D.R.

    2002-10-28

    This document describes a database containing daily observations of maximum and minimum temperature, precipitation amount, snowfall amount, and snow depth from 1062 observing stations across the contiguous US. This database is an expansion and update of the original 138-station database previously released by the Carbon Dioxide Information Analysis Center (CDIAC) as CDIAC numeric data package NDP-042. These 1062 stations are a subset of the 1221-station US Historical Climatology Network (HCN), a monthly database compiled by the National Climatic Data Center (Asheville, North Carolina) that has been widely used in analyzing US climate. Data from 1050 of these daily records extend into the 1990s, while 990 of these extend through 1997. Most station records are essentially complete for at least 40 years; the latest beginning year of record is 1948. Records from 158 stations begin prior to 1900, with that of Charleston, South Carolina beginning the earliest (1871). The daily resolution of these data makes them extremely valuable for studies attempting to detect and monitor long-term climatic changes on a regional scale. Studies using daily data may be able to detect changes in regional climate that would not be apparent from analysis of monthly temperature and precipitation data. Such studies may include analyses of trends in maximum and minimum temperatures, temperature extremes, daily temperature range, precipitation ''event size'' frequency, and the magnitude and duration of wet and dry periods. The data are also valuable in areas such as regional climate model validation and climate change impact assessment. This database is available free of charge from CDIAC as a numeric data package (NDP).

  18. PROTOTIPE SISTEM JARINGAN SENSOR UNTUK MONITORING TEMPERATUR-KELEMBABAN PERMUKAAN DAN BAWAH LAHAN GAMBUT BERBASIS DATABASE

    Directory of Open Access Journals (Sweden)

    Hendra Rosada Nasution

    2016-02-01

    Full Text Available ABSTRAK. Lahan gambut adalah jenis tanah yang terbentuk dari sisa-sisa tumbuhan yang terpendam dalam jangka  waktu yang sangat lama. Lahan gambut memiliki  karakteristik mudah terbakar  pada kondisi panas tertentu yang membentuk bara api di bawah permukaan dan menjalar ke atas permukaan hingga menyebabkan terbakarnya semak belukar atau hutan yang berada di atasnya, sehingga perlu dilakukan monitoring temperatur dan kelembaban permukaan dan bawah lahan gambut. Prototipe yang dibuat terdiri dari dua perangkat transmitter yang dilengkapi dengan sensor sebagai pengukur parameter dan satu perangkat receiver sebagai penerima data kedua transmitter. Pengukuran temperatur tanah di bawah permukaan digunakan sensor LM35 berbentuk probe, kemudian pengukuran temperatur dan kelembaban udara di permukaan digunakan sensor SHT11. pengiriman data dilakukan secara nirkabel menggunakan nRF24L01 dengan jarak maksimal 450 meter dengan jarak yang baik 200 meter. Perangkat receiver dilengkapi sistem interface PC berbasis database pada server  localhost/phpmyadmin. Hasil karakterisasi sensor LM35 dalam bentuk probe menunjukan linieritasnya adalah 0,9994 dan 0,9996; deviasi error 0,380C dan 0,400C; sensitivitas 0,960C dan 0,810C. Hasil lima kali pengukuran pada dua titik pengujian setiap transmitter menunjukkan temperatur tanah memiliki nilai 30,200C - 38,100C dan 24,800C - 38,600C, temperatur udara 25,000C - 38,860C dan 24,850C - 40,150C, kelembaban udara 51,65% - 96,51% dan 43,03% - 96,17%.   Kata kunci : Prototipe, Database, Lahan Gambut, LM35, nRF24L01, SHT11

  19. Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

    Directory of Open Access Journals (Sweden)

    Mingzhu Zhao

    2013-01-01

    Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

  20. National information network and database system of hazardous waste management in China

    Energy Technology Data Exchange (ETDEWEB)

    Ma Hongchang [National Environmental Protection Agency, Beijing (China)

    1996-12-31

    Industries in China generate large volumes of hazardous waste, which makes it essential for the nation to pay more attention to hazardous waste management. National laws and regulations, waste surveys, and manifest tracking and permission systems have been initiated. Some centralized hazardous waste disposal facilities are under construction. China`s National Environmental Protection Agency (NEPA) has also obtained valuable information on hazardous waste management from developed countries. To effectively share this information with local environmental protection bureaus, NEPA developed a national information network and database system for hazardous waste management. This information network will have such functions as information collection, inquiry, and connection. The long-term objective is to establish and develop a national and local hazardous waste management information network. This network will significantly help decision makers and researchers because it will be easy to obtain information (e.g., experiences of developed countries in hazardous waste management) to enhance hazardous waste management in China. The information network consists of five parts: technology consulting, import-export management, regulation inquiry, waste survey, and literature inquiry.

  1. [Study of algorithms to identify schizophrenia in the SNIIRAM database conducted by the REDSIAM network].

    Science.gov (United States)

    Quantin, C; Collin, C; Frérot, M; Besson, J; Cottenet, J; Corneloup, M; Soudry-Faure, A; Mariet, A-S; Roussot, A

    2017-10-01

    The aim of the REDSIAM network is to foster communication between users of French medico-administrative databases and to validate and promote analysis methods suitable for the data. Within this network, the working group "Mental and behavioral disorders" took an interest in algorithms to identify adult schizophrenia in the SNIIRAM database and inventoried identification criteria for patients with schizophrenia in these databases. The methodology was based on interviews with nine experts in schizophrenia concerning the procedures they use to identify patients with schizophrenia disorders in databases. The interviews were based on a questionnaire and conducted by telephone. The synthesis of the interviews showed that the SNIIRAM contains various tables which allow coders to identify patients suffering from schizophrenia: chronic disease status, drugs and hospitalizations. Taken separately, these criteria were not sufficient to recognize patients with schizophrenia, an algorithm should be based on all of them. Apparently, only one-third of people living with schizophrenia benefit from the longstanding disease status. Not all patients are hospitalized, and coding for diagnoses at the hospitalization, notably for short stays in medicine, surgery or obstetrics departments, is not exhaustive. As for treatment with antipsychotics, it is not specific enough as such treatments are also prescribed to patients with bipolar disorders, or even other disorders. It seems appropriate to combine these complementary criteria, while keeping in mind out-patient care (every year 80,000 patients are seen exclusively in an outpatient setting), even if these data are difficult to link with other information. Finally, the experts made three propositions for selection algorithms of patients with schizophrenia. Patients with schizophrenia can be relatively accurately identified using SNIIRAM data. Different combinations of the selected criteria must be used depending on the objectives and

  2. Five years database of landslides and floods affecting Swiss transportation networks

    Science.gov (United States)

    Voumard, Jérémie; Derron, Marc-Henri; Jaboyedoff, Michel

    2017-04-01

    Switzerland is a country threatened by a lot of natural hazards. Many events occur in built environment, affecting infrastructures, buildings or transportation networks and producing occasionally expensive damages. This is the reason why large landslides are generally well studied and monitored in Switzerland to reduce the financial and human risks. However, we have noticed a lack of data on small events which have impacted roads and railways these last years. This is why we have collect all the reported natural hazard events which have affected the Swiss transportation networks since 2012 in a database. More than 800 roads and railways closures have been recorded in five years from 2012 to 2016. These event are classified into six classes: earth flow, debris flow, rockfall, flood, avalanche and others. Data come from Swiss online press articles sorted by Google Alerts. The search is based on more than thirty keywords, in three languages (Italian, French, German). After verifying that the article relates indeed an event which has affected a road or a railways track, it is studied in details. We get finally information on about sixty attributes by event about event date, event type, event localisation, meteorological conditions as well as impacts and damages on the track and human damages. From this database, many trends over the five years of data collection can be outlined: in particular, the spatial and temporal distributions of the events, as well as their consequences in term of traffic (closure duration, deviation, etc.). Even if the database is imperfect (by the way it was built and because of the short time period considered), it highlights the not negligible impact of small natural hazard events on roads and railways in Switzerland at a national level. This database helps to better understand and quantify this events, to better integrate them in risk assessment.

  3. Depression of Glass Transition Temperatures of Polymer Networks by Diluents

    NARCIS (Netherlands)

    Brinke, Gerrit ten; Karasz, Frank E.; Ellis, Thomas S.

    1983-01-01

    A classical thermodynamic theory is used to derive expressions for the depression of the glass transition temperature Tg of a polymer network by a diluent. The enhanced sensitivity of Tg in cross-linked systems to small amounts of diluent is explained. Predictions of the theory are in satisfactory

  4. Application of CAPEC Lipid Property Databases in the Synthesis and Design of Biorefinery Networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona; Cunico, Larissa; Gani, Rafiqul

    Petroleum is currently the primary raw material for the production of fuels and chemicals. Consequently, our society is highly dependent on fossil non-renewable resources. However, renewable raw materials are recently receiving increasing interest for the production of chemicals and fuels, so a n...... of biorefinery networks. The objective of this work is to show the application of databases of physical and thermodynamic properties of lipid components to the synthesis and design of biorefinery networks.......]. The wide variety and complex nature of components in biorefineries poses a challenge with respect to the synthesis and design of these types of processes. Whereas physical and thermodynamic property data or models for petroleum-based processes are widely available, most data and models for biobased...

  5. Experience and Lessons learnt from running high availability databases on Network Attached Storage

    CERN Document Server

    Guijarro, Juan Manuel; Segura Chinchilla, Nilo

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department provides the Oracle based Central Data Base services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been set up. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS as share disk space for RAC purposes and Data hosting. It is composed of two private LAN's to provide access to the NAS file servers and Oracle RAC interconnect, both using network bonding. NAS nodes are configured in partnership to prevent having single points of failure and to provide automatic NAS fail-over. This presentation describes that infrastructure and gives some advice on how to automate its management and setup using a Fabric Management framework such as Quattor. It also covers aspects related with NAS Performance and Monitoring as well Data Backup and Archive of such facility using already existing i...

  6. Quality-controlled sea surface temperature, salinity and other measurements from the NCEI Global Thermosalinographs Database (NCEI-TSG)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection contains global in-situ sea surface temperature (SST), salinity (SSS) and other measurements from the NOAA NCEI Global Thermosalinographs Database...

  7. Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

    Science.gov (United States)

    Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

    2010-11-01

    The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

  8. Analysis of fuel centre temperatures and fission gas release data from the IFPE Database

    International Nuclear Information System (INIS)

    Schubert, A.; Lassmann, K.; Van Uffelen, P.; Van de Laar, J.; Elenkov, D.; Asenov, S.; Boneva, S.; Djourelov, N.; Georgieva, M.

    2003-01-01

    The present work has continued the analysis of fuel centre temperatures and fission gas release, calculated with standard options of the TRANSURANUS code. The calculations are compared to experimental data from the International Fuel Performance Experiments (IFPE) database. It is reported an analysis regarding UO 2 fuel for Western-type reactors: Fuel centre temperatures measured in the experiments Contact 1 and Contact 2 (in-pile tests of 2 rods performed at the Siloe reactor in Grenoble, France, closely simulating commercial PWR conditions); Fission gas release data derived from post-irradiation examinations of 9 fuel rods belonging to the High-Burnup Effects Programme, task 3 (HBEP3). The results allow for a comparison of predictions by TRANSURANUS for the mentioned Western-type fuels with those done previously for Russian-type WWER fuel. The comparison has been extended to include fuel centre temperatures as well as fission gas release. The present version of TRANSURANUS includes a model that calculates the production of Helium. The amount of produced Helium is compared to the measured and to the calculated release of the fission gases Xenon and Krypton

  9. An Analysis of Database Replication Technologies with Regard to Deep Space Network Application Requirements

    Science.gov (United States)

    Connell, Andrea M.

    2011-01-01

    The Deep Space Network (DSN) has three communication facilities which handle telemetry, commands, and other data relating to spacecraft missions. The network requires these three sites to share data with each other and with the Jet Propulsion Laboratory for processing and distribution. Many database management systems have replication capabilities built in, which means that data updates made at one location will be automatically propagated to other locations. This project examines multiple replication solutions, looking for stability, automation, flexibility, performance, and cost. After comparing these features, Oracle Streams is chosen for closer analysis. Two Streams environments are configured - one with a Master/Slave architecture, in which a single server is the source for all data updates, and the second with a Multi-Master architecture, in which updates originating from any of the servers will be propagated to all of the others. These environments are tested for data type support, conflict resolution, performance, changes to the data structure, and behavior during and after network or server outages. Through this experimentation, it is determined which requirements of the DSN can be met by Oracle Streams and which cannot.

  10. Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks.

    Science.gov (United States)

    Balaur, Irina; Mazein, Alexander; Saqi, Mansoor; Lysenko, Artem; Rawlings, Christopher J; Auffray, Charles

    2017-04-01

    The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing. The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/ . The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework . ibalaur@eisbm.org. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  11. ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

    Science.gov (United States)

    Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

    2008-08-12

    New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

  12. The ING Seismic Network Databank (ISND : a friendly parameters and waveform database

    Directory of Open Access Journals (Sweden)

    G. Smriglio

    1995-06-01

    Full Text Available he Istituto Nazionale di Geofisica (ING Seismic Network Database (ISND includes over 300000 arrivaI times of Italian, Mediterranean and teleseismic earthquakes from 1983 to date. This database is a useful tool for Italian and foreign seismologists ( over 1000 data requests in the first 6 months of this year. Recently (1994 the ING began storing in the ISND, the digital waveforms associated with arri,Tal times and experimen- tally allowed users to retrieve waveforms recorded by the ING acquisition system. In this paper we describe the types of data stored and the interactive and batch procedures available to obtain arrivaI times and/or asso- ciated waveforms. The ISND is reachable via telephone line, P.S.I., Internet and DecNet. Users can read and send to their E-mail address alI selected earthquakes locations, parameters, arrivaI times and associated digital waveforms (in SAC, SUDS or ASCII format. For r;aedium or large amounts of data users can ask to receive data by means of magnetic media (DAT, Video 8, floppy disk.

  13. Uniformity factor of temperature difference in heat exchanger networks

    International Nuclear Information System (INIS)

    Chen, Shang; Cui, Guo-min

    2016-01-01

    Highlights: • A uniformity factor of temperature (UFTD) is proposed to heat exchanger network (HEN). • A novel stage-wise superstructure with inner utilities is presented based on UFTD. • New model and DE method is combined as an optimization method. • Optimal HEN structures with inner utilities can be obtained with new method. - Abstract: A uniformity factor of temperature difference (UFTD) is proposed and set up to guide the optimization of Heat exchanger network (HEN). At first, the factor is presented to evaluate the whole enhancement of HEN by handling the logical mean temperature difference as two-dimensional discrete temperature field in system. Then, the factor is applied to different HENs, of which the comparison indicates that a more uniform discrete temperature field leads to a lower UFTD which correlated with a better whole enhancement to improve the optimization level of HEN. A novel stage-wise superstructure model where inner utility can be generated is presented for further analysis of correlation between UFTD and the efficiency of HEN, and more optimal HEN structures can be obtained as inner utility added. Inner utility appears to violate the thermodynamic law, but it makes the discrete temperature field more uniform and improves the heat transfer efficiency of the whole HEN, which brings much more profit than the side effect of inner utility. In sum, the UFTD can not only evaluate the optimization level of the HEN, but also be an optimization object to design new HEN with higher efficiency of energy utilization and lower total annual cost.

  14. Time response of temperature sensors using neural networks

    International Nuclear Information System (INIS)

    Santos, Roberto Carlos dos

    2010-01-01

    In a PWR nuclear power plant, the primary coolant temperature and feedwater temperature are measured using RTDs (Resistance Temperature Detectors). These RTDs typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. The response time of RTDs is characterized by a single parameter called the Plunge Time Constant defined as the time it takes the sensor output to achieve 63.2 percent of its final value after a step change in temperature. Nuclear reactor service conditions are difficult to reproduce in the laboratory, and an in-situ test method called LCSR (Loop Current Step Response) test was developed to measure remotely the response time of RTDs. >From this test, the time constant of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat-transfer model. This calculation is not simple and requires specialized personnel. For this reason an Artificial Neural Network has been developed to predict the time constant of RTD from LCSR test transient. It eliminates the transformations involved in the LCSR application. A series of LCSR tests on RTDs generates the response transients of the sensors, the input data of the networks. Plunge tests are used to determine the time constants of the RTDs, the desired output of the ANN, trained using these sets of input/output data. This methodology was firstly applied to theoretical data simulating 10 RTDs with different time constant values, resulting in an average error of about 0.74 %. Experimental data from three different RTDs was used to predict time constant resulting in a maximum error of 3,34 %. The time constants values predicted from ANN were compared with those obtained from traditional way resulting in an average error of about 18 % and that shows the network is able to predict accurately the sensor time constant. (author)

  15. FunCoup 3.0: database of genome-wide functional coupling networks.

    Science.gov (United States)

    Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L

    2014-01-01

    We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.

  16. GMDH and neural networks applied in temperature sensors monitoring

    International Nuclear Information System (INIS)

    Bueno, Elaine Inacio; Pereira, Iraci Martinez; Silva, Antonio Teixeira e

    2009-01-01

    In this work a monitoring system was developed based on the Group Method of Data Handling (GMDH) and Neural Networks (ANNs) methodologies. This methodology was applied to the IEA-R1 research reactor at IPEN by using a database obtained from a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab GUIDE toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. This methodology was developed by using the GMDH algorithm as input variables to the ANNs. The results obtained using the GMDH and ANNs were better than that obtained using only ANNs. (author)

  17. Teradata University Network: A No Cost Web-Portal for Teaching Database, Data Warehousing, and Data-Related Subjects

    Science.gov (United States)

    Jukic, Nenad; Gray, Paul

    2008-01-01

    This paper describes the value that information systems faculty and students in classes dealing with database management, data warehousing, decision support systems, and related topics, could derive from the use of the Teradata University Network (TUN), a free comprehensive web-portal. A detailed overview of TUN functionalities and content is…

  18. United States Historical Climatology Network (US HCN) monthly temperature and precipitation data

    Energy Technology Data Exchange (ETDEWEB)

    Daniels, R.C. [ed.] [Univ. of Tennessee, Knoxville, TN (United States). Energy, Environment and Resources Center; Boden, T.A. [ed.] [Oak Ridge National Lab., TN (United States); Easterling, D.R.; Karl, T.R.; Mason, E.H.; Hughes, P.Y.; Bowman, D.P. [National Climatic Data Center, Asheville, NC (United States)

    1996-01-11

    This document describes a database containing monthly temperature and precipitation data for 1221 stations in the contiguous United States. This network of stations, known as the United States Historical Climatology Network (US HCN), and the resulting database were compiled by the National Climatic Data Center, Asheville, North Carolina. These data represent the best available data from the United States for analyzing long-term climate trends on a regional scale. The data for most stations extend through December 31, 1994, and a majority of the station records are serially complete for at least 80 years. Unlike many data sets that have been used in past climate studies, these data have been adjusted to remove biases introduced by station moves, instrument changes, time-of-observation differences, and urbanization effects. These monthly data are available free of charge as a numeric data package (NDP) from the Carbon Dioxide Information Analysis Center. The NDP includes this document and 27 machine-readable data files consisting of supporting data files, a descriptive file, and computer access codes. This document describes how the stations in the US HCN were selected and how the data were processed, defines limitations and restrictions of the data, describes the format and contents of the magnetic media, and provides reprints of literature that discuss the editing and adjustment techniques used in the US HCN.

  19. On effective temperature in network models of collective behavior

    International Nuclear Information System (INIS)

    Porfiri, Maurizio; Ariel, Gil

    2016-01-01

    Collective behavior of self-propelled units is studied analytically within the Vectorial Network Model (VNM), a mean-field approximation of the well-known Vicsek model. We propose a dynamical systems framework to study the stochastic dynamics of the VNM in the presence of general additive noise. We establish that a single parameter, which is a linear function of the circular mean of the noise, controls the macroscopic phase of the system—ordered or disordered. By establishing a fluctuation–dissipation relation, we posit that this parameter can be regarded as an effective temperature of collective behavior. The exact critical temperature is obtained analytically for systems with small connectivity, equivalent to low-density ensembles of self-propelled units. Numerical simulations are conducted to demonstrate the applicability of this new notion of effective temperature to the Vicsek model. The identification of an effective temperature of collective behavior is an important step toward understanding order–disorder phase transitions, informing consistent coarse-graining techniques and explaining the physics underlying the emergence of collective phenomena.

  20. Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

    Science.gov (United States)

    Wang, Jiao; Deng, Zhiqiang

    2017-06-01

    A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

  1. Design of Korean nuclear reliability data-base network using a two-stage Bayesian concept

    International Nuclear Information System (INIS)

    Kim, T.W.; Jeong, K.S.; Chae, S.K.

    1987-01-01

    In an analysis of probabilistic risk, safety, and reliability of a nuclear power plant, the reliability data base (DB) must be established first. As the importance of the reliability data base increases, event reporting systems such as the US Nuclear Regulatory Commission's Licensee Event Report and the International Atomic Energy Agency's Incident Reporting System have been developed. In Korea, however, the systematic reliability data base is not yet available. Therefore, foreign data bases have been directly quoted in reliability analyses of Korean plants. In order to develop a reliability data base for Korean plants, the problem is which methodology is to be used, and the application limits of the selected method must be solved and clarified. After starting the commercial operation of Korea Nuclear Unit-1 (KNU-1) in 1978, six nuclear power plants have begun operation. Of these, only KNU-3 is a Canada Deuterium Uranium pressurized heavy-water reactor, and the others are all pressurized water reactors. This paper describes the proposed reliability data-base network (KNRDS) for Korean nuclear power plants in the context of two-stage Bayesian (TSB) procedure of Kaplan. It describes the concept of TSB to obtain the Korean-specific plant reliability data base, which is updated with the incorporation of both the reported generic reliability data and the operation experiences of similar plants

  2. Aspergillus flavus Blast2GO gene ontology database: elevated growth temperature alters amino acid metabolism

    Science.gov (United States)

    The availability of a representative gene ontology (GO) database is a prerequisite for a successful functional genomics study. Using online Blast2GO resources we constructed a GO database of Aspergillus flavus. Of the predicted total 13,485 A. flavus genes 8,987 were annotated with GO terms. The mea...

  3. Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database.

    Science.gov (United States)

    Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi

    2016-11-01

    Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  4. Energetic and Exergetic Analysis of Low and Medium Temperature District Heating Network Integration

    DEFF Research Database (Denmark)

    Li, Hongwei; Svendsen, Svend

    In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can ...... will reduce the amount of water supply from the MTDH network and improve the system energy conversion efficiency. Through the simulation, the system energetic and exergetic efficiencies based on the two network integration approaches were calculated and evaluated.......In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can...... be supplied through upgrading the return water from the MTDH network with a small centralized heat pump. Alternatively, the supply and return water from the MTDH network can be mixed with a shunt at the junction point to supply the LTDH network. Comparing with the second approach, the heat pump system...

  5. Hot metal temperature prediction by neural networks in the blast furnace

    International Nuclear Information System (INIS)

    Cantera, C.; Jimenez, J.; Varela, I.; Formoso, A.

    2002-01-01

    Based on a simplified model, the underlying temperature criteria is proposed as a method to study the temperature trends in a blast furnace. As an application, a neural network able to forecast hot metal temperatures from 2 to 16 h in advance (with decreasing precision) has been built. This neural network has been designed to work at real time in a production plant. (Author)

  6. Incremental View Maintenance for Deductive Graph Databases Using Generalized Discrimination Networks

    Directory of Open Access Journals (Sweden)

    Thomas Beyhl

    2016-12-01

    Full Text Available Nowadays, graph databases are employed when relationships between entities are in the scope of database queries to avoid performance-critical join operations of relational databases. Graph queries are used to query and modify graphs stored in graph databases. Graph queries employ graph pattern matching that is NP-complete for subgraph isomorphism. Graph database views can be employed that keep ready answers in terms of precalculated graph pattern matches for often stated and complex graph queries to increase query performance. However, such graph database views must be kept consistent with the graphs stored in the graph database. In this paper, we describe how to use incremental graph pattern matching as technique for maintaining graph database views. We present an incremental maintenance algorithm for graph database views, which works for imperatively and declaratively specified graph queries. The evaluation shows that our maintenance algorithm scales when the number of nodes and edges stored in the graph database increases. Furthermore, our evaluation shows that our approach can outperform existing approaches for the incremental maintenance of graph query results.

  7. MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS. (1) Quality control

    Science.gov (United States)

    Peña-Angulo, Dhais; Cortesi, Nicola; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; González-Hidalgo, José Carlos

    2014-05-01

    The HIDROCAES project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is focused on the high resolution in the Spanish continental land of the warming processes during the 1951-2010. To do that the Department of Geography (University of Zaragoza, Spain), the Hydrometeorological Service (Brno Division, Chezck Republic) and the ISAC-CNR (Bologna, Italy) are developing the new dataset MOTEDAS (MOnthly TEmperature DAtabase of Spain), from which we present a collection of poster to show (1) the general structure of dataset and quality control; (2) the analyses of spatial correlation of monthly mean values of maximum (Tmax) and minimum (Tmin temperature; (3) the reconstruction processes of series and high resolution grid developing; (4) the first initial results of trend analyses of annual, seasonal and monthly range mean values. MOTEDAS has been created after exhaustive analyses and quality control of the original digitalized data of the Spanish National Meteorological Agency (Agencia Estatal de Meteorología, AEMET). Quality control was applied without any prior reconstruction, i.e. on original series. Then, from the total amount of series stored at AEMet archives (more than 4680) we selected only those series with at least 10 years of data (i.e. 120 months, 3066 series) to apply a quality control and reconstruction processes (see Poster MOTEDAS 3). Length of series was Tmin, upper and lower thresholds of absolute data, etc), and by comparison with reference series (see Poster MOTEDAS 3, about reconstruction). Anomalous data were considered when difference between Candidate and Reference series were higher than three times the interquartile distance. The total amount of monthly suspicious data recognized and discarded at the end of this analyses was 7832 data for Tmin, and 8063 for Tmax data; they represent less than 0,8% of original total monthly data, for both Tmax and Tmin. No spatial pattern was

  8. An Efficient Processing of Join Queries for Sensor Networks Using Column-Oriented Databases

    OpenAIRE

    Kyung-Chang Kim

    2013-01-01

    Recently, the sensor network area is gaining attention both in the industry and academia. Many applications of sensor network such as vehicle tracking and environmental monitoring require joining sensor data scattered over the network. The main performance criterion for queries in a sensor network is to minimize the battery power consumption in each sensor node. Hence, reducing the communication cost of shipping data among sensor nodes is important since it is the main consumer of battery pow...

  9. A Database Query Processing Model in Peer-To-Peer Network ...

    African Journals Online (AJOL)

    Peer-to-peer databases are becoming more prevalent on the internet for sharing and distributing applications, documents, files, and other digital media. The problem associated with answering large-scale ad hoc analysis queries, aggregation queries, on these databases poses unique challenges. This paper presents an ...

  10. The thermodynamic database COST MP0602 for materials for high-temperature lead-free soldering

    Czech Academy of Sciences Publication Activity Database

    Kroupa, Aleš; Dinsdale, A.; Watson, A.; Vřešťál, J.; Zemanová, Adéla; Brož, P.

    2012-01-01

    Roč. 48, č. 3 (2012), s. 339-346 ISSN 1450-5339 R&D Projects: GA MŠk LD11024 Institutional support: RVO:68081723 Keywords : CALPHAD method * lead-free solders * thermodynamic database Subject RIV: BJ - Thermodynamics Impact factor: 1.435, year: 2012

  11. Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database

    Science.gov (United States)

    Brantley, S.; Brazil, L.

    2017-12-01

    The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through tools that are open source and free to use, researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, these tools and data have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing lesson plans, and the resources available to learn more.

  12. Identifying the optimal supply temperature in district heating networks - A modelling approach

    DEFF Research Database (Denmark)

    Mohammadi, Soma; Bojesen, Carsten

    2014-01-01

    of this study is to develop a model for thermo-hydraulic calculation of low temperature DH system. The modelling is performed with emphasis on transient heat transfer in pipe networks. The pseudo-dynamic approach is adopted to model the District Heating Network [DHN] behaviour which estimates the temperature...... dynamically while the flow and pressure are calculated on the basis of steady state conditions. The implicit finite element method is applied to simulate the transient temperature behaviour in the network. Pipe network heat losses, pressure drop in the network and return temperature to the plant...... are calculated in the developed model. The model will serve eventually as a basis to find out the optimal supply temperature in an existing DHN in later work. The modelling results are used as decision support for existing DHN; proposing possible modifications to operate at optimal supply temperature....

  13. Harvesting Covert Networks: The Case Study of the iMiner Database

    DEFF Research Database (Denmark)

    Memon, Nasrullah; Wiil, Uffe Kock; Alhajj, Reda

    2011-01-01

    was incorporated in the iMiner prototype tool, which makes use of investigative data mining techniques to analyse data. This paper will present the developed framework along with the form and structure of the terrorist data in the database. Selected cases will be referenced to highlight the effectiveness of the i...... collected by intelligence agencies and government organisations is inaccessible to researchers. To counter the information scarcity, we designed and built a database of terrorist-related data and information by harvesting such data from publicly available authenticated websites. The database...

  14. NABIC marker database: A molecular markers information network of agricultural crops.

    Science.gov (United States)

    Kim, Chang-Kug; Seol, Young-Joo; Lee, Dong-Jun; Jeong, In-Seon; Yoon, Ung-Han; Lee, Gang-Seob; Hahn, Jang-Ho; Park, Dong-Suk

    2013-01-01

    In 2013, National Agricultural Biotechnology Information Center (NABIC) reconstructs a molecular marker database for useful genetic resources. The web-based marker database consists of three major functional categories: map viewer, RSN marker and gene annotation. It provides 7250 marker locations, 3301 RSN marker property, 3280 molecular marker annotation information in agricultural plants. The individual molecular marker provides information such as marker name, expressed sequence tag number, gene definition and general marker information. This updated marker-based database provides useful information through a user-friendly web interface that assisted in tracing any new structures of the chromosomes and gene positional functions using specific molecular markers. The database is available for free at http://nabic.rda.go.kr/gere/rice/molecularMarkers/

  15. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 2 - Global, 4 km Sea Surface Temperature and Related Thermal Stress Metrics for 1982-2008 (NODC Accession Number 0054501)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  16. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 4 - Global, 4 km Sea Surface Temperature and Related Thermal Stress Metrics for 1981-10-31 to 2010-12-31 (NODC Accession 0087989)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  17. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 3 - Global, 4 km Sea Surface Temperature and Related Thermal Stress Metrics for 1982-2009 (NODC Accession 0068999)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  18. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 2 - Global, 4 km Sea Surface Temperature and Related Thermal Stress Metrics for 1982-2008 (NODC Accession 0054501)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  19. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 5 - Global, 4 km Sea Surface Temperature and Related Thermal Stress Metrics for 1982-2012 (NCEI Accession 0126774)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Version 5 of the Coral Reef Temperature Anomaly Database (CoRTAD) is a global, 4 km, sea surface temperature (SST) and related thermal stress metrics dataset for...

  20. The Coral Reef Temperature Anomaly Database (CoRTAD) Version 1 - Global, 4 km, Sea Surface Temperature and Related Thermal Stress Metrics for 1985-2005 (NODC Accession 0044419)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Coral Reef Temperature Anomaly Database (CoRTAD) is a collection of sea surface temperature (SST) and related thermal stress metrics, developed specifically for...

  1. FoodMicrobionet: A database for the visualisation and exploration of food bacterial communities based on network analysis.

    Science.gov (United States)

    Parente, Eugenio; Cocolin, Luca; De Filippis, Francesca; Zotta, Teresa; Ferrocino, Ilario; O'Sullivan, Orla; Neviani, Erasmo; De Angelis, Maria; Cotter, Paul D; Ercolini, Danilo

    2016-02-16

    Amplicon targeted high-throughput sequencing has become a popular tool for the culture-independent analysis of microbial communities. Although the data obtained with this approach are portable and the number of sequences available in public databases is increasing, no tool has been developed yet for the analysis and presentation of data obtained in different studies. This work describes an approach for the development of a database for the rapid exploration and analysis of data on food microbial communities. Data from seventeen studies investigating the structure of bacterial communities in dairy, meat, sourdough and fermented vegetable products, obtained by 16S rRNA gene targeted high-throughput sequencing, were collated and analysed using Gephi, a network analysis software. The resulting database, which we named FoodMicrobionet, was used to analyse nodes and network properties and to build an interactive web-based visualisation. The latter allows the visual exploration of the relationships between Operational Taxonomic Units (OTUs) and samples and the identification of core- and sample-specific bacterial communities. It also provides additional search tools and hyperlinks for the rapid selection of food groups and OTUs and for rapid access to external resources (NCBI taxonomy, digital versions of the original articles). Microbial interaction network analysis was carried out using CoNet on datasets extracted from FoodMicrobionet: the complexity of interaction networks was much lower than that found for other bacterial communities (human microbiome, soil and other environments). This may reflect both a bias in the dataset (which was dominated by fermented foods and starter cultures) and the lower complexity of food bacterial communities. Although some technical challenges exist, and are discussed here, the net result is a valuable tool for the exploration of food bacterial communities by the scientific community and food industry. Copyright © 2015. Published by

  2. A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

    Directory of Open Access Journals (Sweden)

    Lan Chung-Yu

    2008-09-01

    Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

  3. Geothermal data-base study: mine-water temperatures. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Lawson, D.C.; Sonderegger, J.L.

    1978-07-01

    Investigation of about 1,600 mines and prospects for perennial discharge resulted in the measurement of temperature, pH, specific conductance, and discharge at 80 sites to provide information for a geothermal data base. Measurements were made in the fall, winter, and late spring or early summer to provide information about seasonal variability. None of the temperatures measured exceeded the mean annual air temperature by 15/sup 0/F, but three areas were noted where discharges were anomalously warm, based upon high temperatures, slight temperature variation, and quantity of discharge. The most promising area, at the Gold Bug mine in the Little Rockies, discharges water averaging 7.3/sup 0/C (12.1/sup 0/F) above the mean annual air temperature. The discharge may represent water heated during circulation within the syenite intrusive body. If the syenite is enriched in uranium and thorium, an abnormal amount of heat would be produced by radioactive decay. Alternatively, the water may move through deep permeable sedimentary strata, such as the Madison Group, and be discharged to the surface through fractures in the pluton.

  4. Temperature dependence of the multistability of lactose utilization network of Escherichia coli

    Science.gov (United States)

    Nepal, Sudip; Kumar, Pradeep

    Biological systems are capable of producing multiple states out of a single set of inputs. Multistability acts like a biological switch that allows organisms to respond differently to different environmental conditions and hence plays an important role in adaptation to changing environment. One of the widely studied gene regulatory networks underlying the metabolism of bacteria is the lactose utilization network, which exhibits a multistable behavior as a function of lactose concentration. We have studied the effect of temperature on multistability of the lactose utilization network at various concentrations of thio-methylgalactoside (TMG), a synthetic lactose. We find that while the lactose utilization network exhibits a bistable behavior for temperature T >20° C , a graded response arises for temperature T lactose utilization network as a function of temperature and TMG concentration. Our results suggest that environmental conditions, in this case temperature, can alter the nature of cellular regulation of metabolism.

  5. Optimized district heating supply temperature for large networks; Optimerad framledningstemperatur foer stora fjaerrvaermenaet

    Energy Technology Data Exchange (ETDEWEB)

    Saarinen, Lisa; Boman, Katarina

    2012-02-15

    The supply temperature of the Uppsala district heating network was optimized using a model-based control strategy. Simulation of the network showed that the supply temperature could be decreased by in average 8 deg and the electricity production of the plants supplying the network could be increased with 2.5 % during the period January- April, giving an extra income of 1.2 MSEK due to increased income from electricity sales

  6. Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database.

    Science.gov (United States)

    Allard, Marc W; Strain, Errol; Melka, David; Bunning, Kelly; Musser, Steven M; Brown, Eric W; Timme, Ruth

    2016-08-01

    The FDA has created a United States-based open-source whole-genome sequencing network of state, federal, international, and commercial partners. The GenomeTrakr network represents a first-of-its-kind distributed genomic food shield for characterizing and tracing foodborne outbreak pathogens back to their sources. The GenomeTrakr network is leading investigations of outbreaks of foodborne illnesses and compliance actions with more accurate and rapid recalls of contaminated foods as well as more effective monitoring of preventive controls for food manufacturing environments. An expanded network would serve to provide an international rapid surveillance system for pathogen traceback, which is critical to support an effective public health response to bacterial outbreaks. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  7. BioMart Central Portal: an open database network for the biological community

    Science.gov (United States)

    Guberman, Jonathan M.; Ai, J.; Arnaiz, O.; Baran, Joachim; Blake, Andrew; Baldock, Richard; Chelala, Claude; Croft, David; Cros, Anthony; Cutts, Rosalind J.; Di Génova, A.; Forbes, Simon; Fujisawa, T.; Gadaleta, E.; Goodstein, D. M.; Gundem, Gunes; Haggarty, Bernard; Haider, Syed; Hall, Matthew; Harris, Todd; Haw, Robin; Hu, S.; Hubbard, Simon; Hsu, Jack; Iyer, Vivek; Jones, Philip; Katayama, Toshiaki; Kinsella, R.; Kong, Lei; Lawson, Daniel; Liang, Yong; Lopez-Bigas, Nuria; Luo, J.; Lush, Michael; Mason, Jeremy; Moreews, Francois; Ndegwa, Nelson; Oakley, Darren; Perez-Llamas, Christian; Primig, Michael; Rivkin, Elena; Rosanoff, S.; Shepherd, Rebecca; Simon, Reinhard; Skarnes, B.; Smedley, Damian; Sperling, Linda; Spooner, William; Stevenson, Peter; Stone, Kevin; Teague, J.; Wang, Jun; Wang, Jianxin; Whitty, Brett; Wong, D. T.; Wong-Erasmus, Marie; Yao, L.; Youens-Clark, Ken; Yung, Christina; Zhang, Junjun; Kasprzyk, Arek

    2011-01-01

    BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities. Database URL: http://central.biomart.org. PMID:21930507

  8. The Transformation of Schools' Social Networks during a Data-Based Decision Making Reform

    Science.gov (United States)

    Keuning, Trynke

    2016-01-01

    Context: Collaboration within school teams is considered to be important to build the capacity school teams need to work in a data-based way. In a school characterized by a strong collaborative culture, teachers may have more access to the knowledge and skills for analyzing data, teachers have more opportunity to discuss the performance goals to…

  9. The transformation of schools' social networks during a data-based decision making reform

    NARCIS (Netherlands)

    Keuning, Trynke; Geel, Marieke Van; Visscher, Adrie; Fox, Jean Paul; Moolenaar, Nienke M.|info:eu-repo/dai/nl/304352802

    2016-01-01

    Context: Collaboration within school teams is considered to be important to build the capacity school teams need to work in a data-based way. In a school characterized by a strong collaborative culture, teachers may have more access to the knowledge and skills for analyzing data, teachers have more

  10. Materials Properties Database for Selection of High-Temperature Alloys and Concepts of Alloy Design for SOFC Applications

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Z Gary; Paxton, Dean M.; Weil, K. Scott; Stevenson, Jeffry W.; Singh, Prabhakar

    2002-11-24

    To serve as an interconnect / gas separator in an SOFC stack, an alloy should demonstrate the ability to provide (i) bulk and surface stability against oxidation and corrosion during prolonged exposure to the fuel cell environment, (ii) thermal expansion compatibility with the other stack components, (iii) chemical compatibility with adjacent stack components, (iv) high electrical conductivity of the surface reaction products, (v) mechanical reliability and durability at cell exposure conditions, (vii) good manufacturability, processability and fabricability, and (viii) cost effectiveness. As the first step of this approach, a composition and property database was compiled for high temperature alloys in order to assist in determining which alloys offer the most promise for SOFC interconnect applications in terms of oxidation and corrosion resistance. The high temperature alloys of interest included Ni-, Fe-, Co-base superal

  11. Wireless sensor networks for canopy temperature sensing and irrigation management

    Science.gov (United States)

    For researchers, canopy temperature measurements have proven useful in characterizing crop water stress and developing protocols for irrigation management. Today, there is heightened interest in using remote canopy temperature measurements for real-time irrigation scheduling. However, without the us...

  12. Global Historical Climatology Network - Monthly Temperature, Version 4 (BETA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Only available as BETA release. The GHCN-Monthly Temperature Version 4 dataset consists of monthly mean temperature - both raw and bias corrected data. A full...

  13. Development of Bioclimatic Design Tool for Oman Using Dry Bulb and Dew Point Temperatures Open Database

    Directory of Open Access Journals (Sweden)

    Nasser Al-Azri

    2017-06-01

    Full Text Available Bioclimatic charts are used by engineers and architects in implementing passive cooling systems and architectural optimization with respect to natural air conditioning. Conventionally, the development of these charts is based on the availability of typical meteorological year which requires a record of meteorological data that are rarely available in sufficient amounts. Bioclimatic charts in Oman were developed earlier by the authors for limited locations based on the available typical meteorological years. Using dry bulb and dew point temperatures only, bioclimatic charts are developed for Adam, Buraimi, Ibra, Muscat, Nizwa, Rustaq, Saiq, Salalah, Suhar and Sur. These charts are better representative of bioclimatic trends since their development is mainly based on the relevant parameters, namely dry bulb temperature and dew point.

  14. [Geothermal system temperature-depth database and model for data analysis]. 5. quarterly technical progress report

    Energy Technology Data Exchange (ETDEWEB)

    Blackwell, D.D.

    1998-04-25

    During this first quarter of the second year of the contract activity has involved several different tasks. The author has continued to work on three tasks most intensively during this quarter: the task of implementing the data base for geothermal system temperature-depth, the maintenance of the WWW site with the heat flow and gradient data base, and finally the development of a modeling capability for analysis of the geothermal system exploration data. The author has completed the task of developing a data base template for geothermal system temperature-depth data that can be used in conjunction with the regional data base that he had already developed and is now implementing it. Progress is described.

  15. New paleoclimatic database for the Iberian Peninsula since AD 1700 inferred from tree-ring records and documentary evidence: advances in temperature and drought variability reconstructions

    Science.gov (United States)

    Tejedor, Ernesto; Ángel Saz, Miguel; de Luis, Martín; Esper, Jan; Barriendos, Mariano; Serrano-Notivoli, Roberto; Novak, Klemen; Longares, Luis Alberto; Martínez-del Castillo, Edurne; María Cuadrat, José

    2017-04-01

    A substantial increase of surface air temperatures in the upcoming decades, particularly significant in the Mediterranean basin, has been reported by the IPCC (IPCC, 2013). It is therefore particularly important to study past climate extremes and variability in this region, which will in turn support the accuracy of future climate scenarios. Yet, our knowledge of past climate variability and trends is limited by the shortage of instrumental data prior to the twentieth century, which prompts to the need of discovering new sources with which to reconstruct past climate. We here present a new paleoclimatic database for the northeast of the Iberian Peninsula based on tree-ring records, documentary evidence and instrumental data. The network includes 774 tree-ring, earlywood and latewood width series from Pinus uncinata, Pinus sylvestris and Pinus nigra trees in the Pyrenees and Iberian Range reaching back to AD 1510. Three reconstructions are developed using these samples; an annual drought reconstruction since AD 1694, a summer drought reconstruction since AD 1734, and a maximum temperature reconstruction since AD 1604. Additionally, the documentary records from 16 locations in the Ebro Valley are examined focusing on climate-related 'rogations'. We differentiated three types of rogations, considering the importance of religious acts, to identify the severity of drought and pluvial events. Finally, an attempt to explore the links between documentary and tree-ring based reconstructions is presented.

  16. A computer network system for mutual usage four databases of nuclear materials (Data-Free-Way)

    International Nuclear Information System (INIS)

    Fujita, M.; Kurihara, Y.; Shindou, M.; Yokoyama, N.; Tachi, Y.; Kano, S.; Iwata, S.

    1996-01-01

    Distributed database system named 'Data-Free-Way' for advanced nuclear materials has been developed by National Research Institute for Metals (NRIM), Japan Atomic Energy Research Institute (JAERI) and Power Reactor and Nuclear Fuel Development Corporation (PNC) under cooperation agreement between these three organizations. In the paper, features and functions of the system including input data are described together with method to share database among the three organizations as well as examples of the easy accessible search of material properties. Results of analysis of tensile and creep properties data on type 316 stainless steel collected by the different organizations and stored in the present system are also introduced as an example of attractive utilization of the system. Moreover, in order to consider the system in near future, some trails of WWW server of several sites in 'Data-Free-Way' to supply the information on nuclear materials to Internet are introduced. (author)

  17. BioMart Central Portal: an open database network for the biological community

    OpenAIRE

    Guberman, Jonathan M.; Ai, J.; Arnaiz, O.; Baran, Joachim; Blake, Andrew; Baldock, Richard; Chelala, Claude; Croft, David; Cros, Anthony; Cutts, Rosalind J.; Di Genova, A.; Forbes, Simon; Fujisawa, T.; Gadaleta, E.; Goodstein, D. M.

    2011-01-01

    International audience; BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common inte...

  18. Toward a standardized soil carbon database platform in the US Critical Zone Observatory Network

    Science.gov (United States)

    Filley, T. R.; Marini, L.; Todd-Brown, K. E.; Malhotra, A.; Harden, J. W.; Kumar, P.

    2017-12-01

    Within the soil carbon community of the US Critical Zone Observatory (CZO) Network, efforts are underway to promote network-level data syntheses and modeling projects and to identify barriers to data intercomparability. This represents a challenging goal given the diversity of soil carbon sampling methodologies, spatial and vertical resolution, carbon pool isolation protocols, subsequent measurement techniques, and matrix terminology. During the last annual meeting of the CZO SOC Working Group, Dec 11, 2016, it was decided that integration with, and potentially adoption of, a widely used, active, and mature data aggregation, archival, and visualization platform was the easiest route to achieve this ultimate goal. Additionally, to assess the state of deep and shallow soil C data among the CZO sites it was recommended that a comprehensive survey must be undertaken to identify data gaps and catalog the various soil sampling and analysis methodologies. The International Soil Carbon Network (ISCN) has a long history of leadership in the development of soil C data aggregation, archiving, and visualization tools and currently houses data for over 70,000 soil cores contributed from international soil carbon community. Over the past year, members of the CZO network and the ISCN have met to discuss logistics of adopting the ISCN template within the CZO. Collaborative efforts among all of the CZO site data managers, led by the Intensively Managed Landscapes CZO, will evaluate feasibility of adoption of the ISCN template, or some modification thereof, and distribution to the appropriate soil scientists for data upload and aggregation. Partnering with ISCN also ensures that soil characteristics from the US CZO are placed in a developing global soil context and paves the way for future integration of data from other international CZO networks. This poster will provide an update of this overall effort along with a summary of data products, partnering networks, and recommendations

  19. Establishment of database and network for research of stream generator and state of the art technology review

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Jae Bong; Hur, Nam Su; Moon, Seong In; Seo, Hyeong Won; Park, Bo Kyu; Park, Sung Ho; Kim, Hyung Geun [Sungkyunkwan Univ., Seoul (Korea, Republic of)

    2004-02-15

    A significant number of steam generator tubes are defective and are removed from service or repaired world widely. This wide spread damage has been caused by diverse degradation mechanisms, some of which are difficult to detect and predict. Regarding domestic nuclear power plants, also, the increase of number of operating nuclear power plants and operating periods may result in the increase of steam generator tube failure. So, it is important to carry out the integrity evaluation process to prevent the steam generator tube damage. There are two objectives of this research. The one is to make database for the research of steam generator at domestic research institution. It will increase the efficiency and capability of limited domestic research resources by sharing data and information through network organization. Also, it will enhance the current standard of integrity evaluation procedure that is considerably conservative but can be more reasonable. The second objective is to establish the standard integrity evaluation procedure for steam generator tube by reviewing state of the art technology. The research resources related to steam generator tubes are managed by the established web-based database system. The following topics are covered in this project: development of web-based network for research on steam generator tubes review of state of the art technology.

  20. Establishment of database and network for research of stream generator and state of the art technology review

    International Nuclear Information System (INIS)

    Choi, Jae Bong; Hur, Nam Su; Moon, Seong In; Seo, Hyeong Won; Park, Bo Kyu; Park, Sung Ho; Kim, Hyung Geun

    2004-02-01

    A significant number of steam generator tubes are defective and are removed from service or repaired world widely. This wide spread damage has been caused by diverse degradation mechanisms, some of which are difficult to detect and predict. Regarding domestic nuclear power plants, also, the increase of number of operating nuclear power plants and operating periods may result in the increase of steam generator tube failure. So, it is important to carry out the integrity evaluation process to prevent the steam generator tube damage. There are two objectives of this research. The one is to make database for the research of steam generator at domestic research institution. It will increase the efficiency and capability of limited domestic research resources by sharing data and information through network organization. Also, it will enhance the current standard of integrity evaluation procedure that is considerably conservative but can be more reasonable. The second objective is to establish the standard integrity evaluation procedure for steam generator tube by reviewing state of the art technology. The research resources related to steam generator tubes are managed by the established web-based database system. The following topics are covered in this project: development of web-based network for research on steam generator tubes review of state of the art technology

  1. Inferring pregnancy episodes and outcomes within a network of observational databases.

    Directory of Open Access Journals (Sweden)

    Amy Matcho

    Full Text Available Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE, Truven MarketScan® Multi-state Medicaid (MDCD, and the Optum ClinFormatics® (Optum database and one non-US database, the United Kingdom (UK based Clinical Practice Research Datalink (CPRD. Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm's Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99-100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95-100%, while start date agreement within seven days in either direction ranged from 90-97%. In Optum validation sensitivity analysis, a total of 73% of

  2. Inferring pregnancy episodes and outcomes within a network of observational databases

    Science.gov (United States)

    Ryan, Patrick; Fife, Daniel; Gifkins, Dina; Knoll, Chris; Friedman, Andrew

    2018-01-01

    Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE), Truven MarketScan® Multi-state Medicaid (MDCD), and the Optum ClinFormatics® (Optum) database and one non-US database, the United Kingdom (UK) based Clinical Practice Research Datalink (CPRD). Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm’s Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99–100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95–100%, while start date agreement within seven days in either direction ranged from 90–97%. In Optum validation sensitivity analysis, a total of 73% of

  3. Biomine: predicting links between biological entities using network models of heterogeneous databases

    Directory of Open Access Journals (Sweden)

    Eronen Lauri

    2012-06-01

    Full Text Available Abstract Background Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases. Results Biomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes. Conclusions The experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable

  4. Networked neuroscience : brain scans and visual knowing at the intersection of atlases and databases

    NARCIS (Netherlands)

    Beaulieu, Anne; de Rijcke, Sarah; Coopmans, Catelijne; Woolgar, Steve

    2014-01-01

    This chapter discusses the development of authoritative collections of brain scans known as “brain atlases”, focusing in particular on how such scans are constituted as authoritative visual objects. Three dimensions are identified: first, brain scans are parts of suites of networked technologies

  5. Network performance of a wireless sensor network for temperature monitoring in vineyards

    DEFF Research Database (Denmark)

    Liscano, Ramiro; Jacoub, John Khalil; Dersingh, Anand

    2011-01-01

    Wireless sensor networks (WSNs) are an emerging technology which can be used for outdoor environmental monitoring. This paper presents challenges that arose from the development and deployment of a WSN for environmental monitoring as well as network performance analysis of this network. Different...... components in our sensor network architecture are presented like the physical nodes, the sensor node code, and two messaging protocols; one for collecting sensor and network values and the other for sensor node commands. An information model for sensor nodes to support plug-and-play capabilities in sensor...... networks is also presented....

  6. The GTN-P Data Management System: A central database for permafrost monitoring parameters of the Global Terrestrial Network for Permafrost (GTN-P) and beyond

    Science.gov (United States)

    Lanckman, Jean-Pierre; Elger, Kirsten; Karlsson, Ævar Karl; Johannsson, Halldór; Lantuit, Hugues

    2013-04-01

    Permafrost is a direct indicator of climate change and has been identified as Essential Climate Variable (ECV) by the global observing community. The monitoring of permafrost temperatures, active-layer thicknesses and other parameters has been performed for several decades already, but it was brought together within the Global Terrestrial Network for Permafrost (GTN-P) in the 1990's only, including the development of measurement protocols to provide standardized data. GTN-P is the primary international observing network for permafrost sponsored by the Global Climate Observing System (GCOS) and the Global Terrestrial Observing System (GTOS), and managed by the International Permafrost Association (IPA). All GTN-P data was outfitted with an "open data policy" with free data access via the World Wide Web. The existing data, however, is far from being homogeneous: it is not yet optimized for databases, there is no framework for data reporting or archival and data documentation is incomplete. As a result, and despite the utmost relevance of permafrost in the Earth's climate system, the data has not been used by as many researchers as intended by the initiators of the programs. While the monitoring of many other ECVs has been tackled by organized international networks (e.g. FLUXNET), there is still no central database for all permafrost-related parameters. The European Union project PAGE21 created opportunities to develop this central database for permafrost monitoring parameters of GTN-P during the duration of the project and beyond. The database aims to be the one location where the researcher can find data, metadata, and information of all relevant parameters for a specific site. Each component of the Data Management System (DMS), including parameters, data levels and metadata formats were developed in cooperation with the GTN-P and the IPA. The general framework of the GTN-P DMS is based on an object oriented model (OOM), open for as many parameters as possible, and

  7. DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

    Directory of Open Access Journals (Sweden)

    Prashanthi Karyala

    2016-09-01

    Full Text Available Dengue virus (DENV is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/.

  8. DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.

    Science.gov (United States)

    Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma

    2016-09-01

    Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).

  9. Establishing the ACORN National Practitioner Database: Strategies to Recruit Practitioners to a National Practice-Based Research Network.

    Science.gov (United States)

    Adams, Jon; Steel, Amie; Moore, Craig; Amorin-Woods, Lyndon; Sibbritt, David

    2016-10-01

    The purpose of this paper is to report on the recruitment and promotion strategies employed by the Australian Chiropractic Research Network (ACORN) project aimed at helping recruit a substantial national sample of participants and to describe the features of our practice-based research network (PBRN) design that may provide key insights to others looking to establish a similar network or draw on the ACORN project to conduct sub-studies. The ACORN project followed a multifaceted recruitment and promotion strategy drawing on distinct branding, a practitioner-focused promotion campaign, and a strategically designed questionnaire and distribution/recruitment approach to attract sufficient participation from the ranks of registered chiropractors across Australia. From the 4684 chiropractors registered at the time of recruitment, the project achieved a database response rate of 36% (n = 1680), resulting in a large, nationally representative sample across age, gender, and location. This sample constitutes the largest proportional coverage of participants from any voluntary national PBRN across any single health care profession. It does appear that a number of key promotional and recruitment features of the ACORN project may have helped establish the high response rate for the PBRN, which constitutes an important sustainable resource for future national and international efforts to grow the chiropractic evidence base and research capacity. Further rigorous enquiry is needed to help evaluate the direct contribution of specific promotional and recruitment strategies in attaining high response rates from practitioner populations who may be invited to participate in future PBRNs. Copyright © 2016. Published by Elsevier Inc.

  10. PERANCANGAN MODEL NETWORK PADA MESIN DATABASE NON SPATIAL UNTUK MANUVER JARINGAN LISTRIK SEKTOR DISTRIBUSI DENGAN PL SQ

    Directory of Open Access Journals (Sweden)

    I Made Sukarsa

    2009-06-01

    Full Text Available Saat ini aplikasi di bidang SIG telah banyak yang dikembangkan berbasis mesin DBMS (Database Management System non spatial sehingga mampu mendukung model penyajian data secara client server dan menangani data dalam jumlah yang besar. Salah satunya telah dikembangkan untuk menangani data jaringan listrik.Kenyataannya, mesin-mesin DBMS belum dilengkapi dengan kemampuan untuk melakukan analisis network seperti manuver jaringan dan merupakan dasar untuk pengembangan berbagai aplikasi lainnya. Oleh karena itu,perlu dikembangkan suatu model network untuk manuver jaringan listrik dengan berbagai kekhasannya.Melalui beberapa tahapan penelitian yang dilakukan, telah dapat dikembangkan suatu model network yangdapat digunakan untuk menangani manuver jaringan. Model ini dibangun dengan memperhatikan kepentingan pengintegrasian dengan sistem eksisting dengan meminimalkan adanya perubahan pada aplikasi eksisting.Pemilihan implementasi berbasis PL SQL (Pragrammable Language Structure Query Language akan memberikan berbagai keuntungan termasuk unjuk kerja sistem. Model ini telah diujikan untuk simulasi pemadaman,menghitung perubahan struktur pembebanan jaringan dan dapat dikembangkan untuk analisis sistem tenaga listrik seperti rugi-rugi, load flow dan sebagainya sehingga pada akhirnya aplikasi SIG akan mampu mensubstitusi danmengatasi kelemahan aplikasi analisis sistem tenaga yang banyak dipakai saat ini seperti EDSA (Electrical DesignSystem Anaysis .

  11. Equivalent network for resistance and temperature coefficient of resistance versus temperature and composition of thick resistive films

    International Nuclear Information System (INIS)

    Kusy, A.

    1987-01-01

    Two types of elementary resistances in thick resistive films have been considered: (i) constriction resistance R/sub C/ determined by the bulk properties of conducting material and by the geometry of constriction, and (ii) barrier resistance R/sub B/ determined by the parameters of a thermally activated type of tunneling process and by the geometry of the metal-insulator-metal unit. On this basis a resistance network composed of a large number of the two types of resistances has been defined. The network has been considered as being equivalent to thick resistive film (TRF) from the point of view of the resistance and temperature coefficient of resistance (TCR). The parameters of this network have been evaluated by the computer-aided approximation of the experimental data found for RuO 2 -based TRFs. On the basis of the equations derived for the network as well as the results of the approximation process, it can be concluded that the small values of the network TCR result from the superposition of the TCR of the conducting component β/sub C/ and of the temperature coefficient of barrier resistance α/sub B/. In this superposition β/sub C/ is attenuated (by 1--2 orders of magnitude), while α/sub B/ is attenuated by only few percentages. The network has been found to be strongly barrier dominated

  12. Prediction of fracture toughness temperature dependence applying neural network

    Czech Academy of Sciences Publication Activity Database

    Dlouhý, Ivo; Hadraba, Hynek; Chlup, Zdeněk; Šmída, T.

    2011-01-01

    Roč. 11, č. 1 (2011), s. 9-14 ISSN 1451-3749 R&D Projects: GA ČR(CZ) GAP108/10/0466 Institutional research plan: CEZ:AV0Z20410507 Keywords : brittle to ductile transition * fracture toughness * artificial neural network * steels Subject RIV: JL - Materials Fatigue, Friction Mechanics

  13. Improving thermal performance of an existing UK district heat network: a case for temperature optimization

    DEFF Research Database (Denmark)

    Tunzi, Michele; Boukhanouf, Rabah; Li, Hongwei

    2018-01-01

    This paper presents results of a research study into improving energy performance of small-scale district heat network through water supply and return temperature optimization technique. The case study involves establishing the baseline heat demand of the estate’s buildings, benchmarking...... the existing heat network operating parameters, and defining the optimum supply and return temperature. A stepwise temperature optimization technique of plate radiators heat emitters was applied to control the buildings indoor thermal comfort using night set back temperature strategy of 21/18 °C....... It was established that the heat network return temperature could be lowered from the current measured average of 55 °C to 35.6 °C, resulting in overall reduction of heat distribution losses and fuel consumption of 10% and 9% respectively. Hence, the study demonstrates the potential of operating existing heat...

  14. Branched carbon nanofiber network synthesis at room temperature using radio frequency supported microwave plasmas

    International Nuclear Information System (INIS)

    Boskovic, Bojan O.; Stolojan, Vlad; Zeze, Dagou A.; Forrest, Roy D.; Silva, S. Ravi P.; Haq, Sajad

    2004-01-01

    Carbon nanofibers have been grown at room temperature using a combination of radio frequency and microwave assisted plasma-enhanced chemical vapor deposition. The nanofibers were grown, using Ni powder catalyst, onto substrates kept at room temperature by using a purposely designed water-cooled sample holder. Branched carbon nanofiber growth was obtained without using a template resulting in interconnected carbon nanofiber network formation on substrates held at room temperature. This method would allow room-temperature direct synthesized nanofiber networks over relatively large areas, for a range of temperature sensitive substrates, such as organic materials, plastics, and other polymers of interest for nanoelectronic two-dimensional networks, nanoelectromechanical devices, nanoactuators, and composite materials

  15. Load forecasting method considering temperature effect for distribution network

    Directory of Open Access Journals (Sweden)

    Meng Xiao Fang

    2016-01-01

    Full Text Available To improve the accuracy of load forecasting, the temperature factor was introduced into the load forecasting in this paper. This paper analyzed the characteristics of power load variation, and researched the rule of the load with the temperature change. Based on the linear regression analysis, the mathematical model of load forecasting was presented with considering the temperature effect, and the steps of load forecasting were given. Used MATLAB, the temperature regression coefficient was calculated. Using the load forecasting model, the full-day load forecasting and time-sharing load forecasting were carried out. By comparing and analyzing the forecast error, the results showed that the error of time-sharing load forecasting method was small in this paper. The forecasting method is an effective method to improve the accuracy of load forecasting.

  16. Network of TAMCNS: Identifying Influence Regions Within the GCSS-MC Database

    Science.gov (United States)

    2017-06-01

    friendship. You made spending many hours at NPS an enjoyable experience. In particular, I want to acknowledge Dan for his assistance with math and LaTeX...Hall, 2001. [7] K. H. Rosen, Discrete Mathematics and Its Applications, 7th ed. New York, NY: McGraw-Hill, 2012. [8] D. Ortiz-Arroyo, “Discovering sets...observations/whats-a-voxel-and-what-can-it-tell-us-a-primer-on-fmri/ [28] A. Beveridge and J. Shan, “Network of thrones,” Math Horizons, vol. 23, no. 4

  17. SISSY: An example of a multi-threaded, networked, object-oriented databased application

    International Nuclear Information System (INIS)

    Scipioni, B.; Liu, D.; Song, T.

    1993-05-01

    The Systems Integration Support SYstem (SISSY) is presented and its capabilities and techniques are discussed. It is fully automated data collection and analysis system supporting the SSCL's systems analysis activities as they relate to the Physics Detector and Simulation Facility (PDSF). SISSY itself is a paradigm of effective computing on the PDSF. It uses home-grown code (C++), network programming (RPC, SNMP), relational (SYBASE) and object-oriented (ObjectStore) DBMSs, UNIX operating system services (IRIX threads, cron, system utilities, shells scripts, etc.), and third party software applications (NetCentral Station, Wingz, DataLink) all of which act together as a single application to monitor and analyze the PDSF

  18. SPAN: A Network Providing Integrated, End-to-End, Sensor-to-Database Solutions for Environmental Sciences

    Science.gov (United States)

    Benzel, T.; Cho, Y. H.; Deschon, A.; Gullapalli, S.; Silva, F.

    2009-12-01

    In recent years, advances in sensor network technology have shown great promise to revolutionize environmental data collection. Still, wide spread adoption of these systems by domain experts has been lacking, and these have remained the purview of the engineers who design them. While there are many data logging options for basic data collection in the field currently, scientists are often required to visit the deployment sites to retrieve their data and manually import it into spreadsheets. Some advanced commercial software systems do allow scientists to collect data remotely, but most of these systems only allow point-to-point access, and require proprietary hardware. Furthermore, these commercial solutions preclude the use of sensors from other manufacturers or integration with internet based database repositories and compute engines. Therefore, scientists often must download and manually reformat their data before uploading it to the repositories if they wish to share their data. We present an open-source, low-cost, extensible, turnkey solution called Sensor Processing and Acquisition Network (SPAN) which provides a robust and flexible sensor network service. At the deployment site, SPAN leverages low-power generic embedded processors to integrate variety of commercially available sensor hardware to the network of environmental observation systems. By bringing intelligence close to the sensed phenomena, we can remotely control configuration and re-use, establish rules to trigger sensor activity, manage power requirements, and control the two-way flow of sensed data as well as control information to the sensors. Key features of our design include (1) adoption of a hardware agnostic architecture: our solutions are compatible with several programmable platforms, sensor systems, communication devices and protocols. (2) information standardization: our system supports several popular communication protocols and data formats, and (3) extensible data support: our

  19. Application and Simulation of Fuzzy Neural Network PID Controller in the Aircraft Cabin Temperature

    Directory of Open Access Journals (Sweden)

    Ding Fang

    2013-06-01

    Full Text Available Considering complex factors of affecting ambient temperature in Aircraft cabin, and some shortages of traditional PID control like the parameters difficult to be tuned and control ineffective, this paper puts forward the intelligent PID algorithm that makes fuzzy logic method and neural network together, scheming out the fuzzy neural net PID controller. After the correction of the fuzzy inference and dynamic learning of neural network, PID parameters of the controller get the optimal parameters. MATLAB simulation results of the cabin temperature control model show that the performance of the fuzzy neural network PID controller has been greatly improved, with faster response, smaller overshoot and better adaptability.

  20. Exergetic evaluation of heat pump booster configurations in a low temperature district heating network

    DEFF Research Database (Denmark)

    Ommen, Torben Schmidt; Elmegaard, Brian

    2012-01-01

    In order to minimise losses in a district heating network, one approach is to lower the temperature difference between working media and soil. Considering only direct heat exchange, the minimum forward temperature level is determined by the demand side, as energy services are required at a certai...

  1. Foreground removal from WMAP 5 yr temperature maps using an MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik

    2010-01-01

    CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. Methods. The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5...... yr temperature data without using any auxiliary data. Results. A simple multilayer perceptron neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also......, the systematic errors, i.e. errors correlated with the Galactic foregrounds, are very small. Conclusions. With these results the neural network method is well prepared for dealing with the high-quality CMB data from the ESA Planck Surveyor satellite. © ESO, 2010....

  2. Database management for an electrical distribution network of intermediate complexity CERN

    CERN Document Server

    De Ruschi, Daniele; Burdet, Georges

    2010-01-01

    This thesis is submitted as the final work for the degree of Master of Science in Engineering of Information that has been taken by the writer at at University of Bergamo, Italy. The report is based on the work conducted by the writer from September 2009 throughout June 2010 on a project assignment given by the department of Engineering Electrical Control at CERN Genève The work performed is a contribution to the GESMAR system of CERN. GESMAR is a CERN made complex platform for support and management of electric network. In this work is developed an information system for an ETL process. The report presents the design, implementation and evaluation made, prototypes of applications which take advantages of new information inserted in GESMAR are also presented.

  3. Temperature prediction model of asphalt pavement in cold regions based on an improved BP neural network

    International Nuclear Information System (INIS)

    Xu, Bo; Dan, Han-Cheng; Li, Liang

    2017-01-01

    Highlights: • Pavement temperature prediction model is presented with improved BP neural network. • Dynamic and static methods are presented to predict pavement temperature. • Pavement temperature can be excellently predicted in next 3 h. - Abstract: Ice cover on pavement threatens traffic safety, and pavement temperature is the main factor used to determine whether the wet pavement is icy or not. In this paper, a temperature prediction model of the pavement in winter is established by introducing an improved Back Propagation (BP) neural network model. Before the application of the BP neural network model, many efforts were made to eliminate chaos and determine the regularity of temperature on the pavement surface (e.g., analyze the regularity of diurnal and monthly variations of pavement temperature). New dynamic and static prediction methods are presented by improving the algorithms to intelligently overcome the prediction inaccuracy at the change point of daily temperature. Furthermore, some scenarios have been compared for different dates and road sections to verify the reliability of the prediction model. According to the analysis results, the daily pavement temperatures can be accurately predicted for the next 3 h from the time of prediction by combining the dynamic and static prediction methods. The presented method in this paper can provide technical references for temperature prediction of the pavement and the development of an early-warning system for icy pavements in cold regions.

  4. Foreground removal from CMB temperature maps using an MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik; Jørgensen, H.E.

    2008-01-01

    the CMB temperature signal from the combined signal CMB and the foregrounds has been investigated. As a specific example, we have analysed simulated data, as expected from the ESA Planck CMB mission. A simple multilayer perceptron neural network with 2 hidden layers can provide temperature estimates over...... CMB signal it is essential to minimize the systematic errors in the CMB temperature determinations. Following the available knowledge of the spectral behavior of the Galactic foregrounds simple power law-like spectra have been assumed. The feasibility of using a simple neural network for extracting...

  5. A highly crystalline single Au wire network as a high temperature transparent heater

    Science.gov (United States)

    Rao, K. D. M.; Kulkarni, Giridhar U.

    2014-05-01

    A transparent conductor which can generate high temperatures finds important applications in optoelectronics. In this article, a wire network made of Au on quartz is shown to serve as an effective high temperature transparent heater. The heater has been fabricated by depositing Au onto a cracked sacrificial template. The highly interconnected Au wire network thus formed exhibited a transmittance of ~87% in a wide spectral range with a sheet resistance of 5.4 Ω □-1. By passing current through the network, it could be joule heated to ~600 °C within a few seconds. The extraordinary thermal performance and stability owe much to the seamless junctions present in the wire network. Furthermore, the wire network gets self-annealed through joule heating as seen from its increased crystallinity. Interestingly, both transmittance and sheet resistance improved following annealing to 92% and 3.2 Ω □-1, respectively. A transparent conductor which can generate high temperatures finds important applications in optoelectronics. In this article, a wire network made of Au on quartz is shown to serve as an effective high temperature transparent heater. The heater has been fabricated by depositing Au onto a cracked sacrificial template. The highly interconnected Au wire network thus formed exhibited a transmittance of ~87% in a wide spectral range with a sheet resistance of 5.4 Ω □-1. By passing current through the network, it could be joule heated to ~600 °C within a few seconds. The extraordinary thermal performance and stability owe much to the seamless junctions present in the wire network. Furthermore, the wire network gets self-annealed through joule heating as seen from its increased crystallinity. Interestingly, both transmittance and sheet resistance improved following annealing to 92% and 3.2 Ω □-1, respectively. Electronic supplementary information (ESI) available: Optical micrographs, EDAX, XRD, SEM and TEM images of Au metal wires. See DOI: 10.1039/c4nr00869c

  6. Short-term PV/T module temperature prediction based on PCA-RBF neural network

    Science.gov (United States)

    Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

    2018-02-01

    Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

  7. Branched carbon nanofiber network synthesis at room temperature using radio frequency supported microwave plasmas

    OpenAIRE

    Boskovic, BO; Stolojan, V; Zeze, DA; Forrest, RD; Silva, SRP; Haq, S

    2004-01-01

    Carbon nanofibers have been grown at room temperature using a combination of radio frequency and microwave assisted plasma-enhanced chemical vapor deposition. The nanofibers were grown, using Ni powder catalyst, onto substrates kept at room temperature by using a purposely designed water-cooled sample holder. Branched carbon nanofiber growth was obtained without using a template resulting in interconnected carbon nanofiber network formation on substrates held at room temperatur...

  8. Data-Based Energy Efficient Clustered Routing Protocol for Wireless Sensors Networks – Tabuk Flood Monitoring System Case Study

    Directory of Open Access Journals (Sweden)

    Ammar Babiker

    2017-10-01

    Full Text Available Energy efficiency has been considered as the most important issue in wireless sensor networks. As in many applications, wireless sensors are scattered in a wide harsh area, where the battery replacement or charging will be quite difficult and it is the most important challenge. Therefore, the design of energy saving mechanism becomes mandatory in most recent research. In this paper, a new energy efficient clustered routing protocol is proposed: the proposed protocol is based on analyzing the data collected from the sensors in a base-station. Based on this analysis the cluster head will be selected as the one with the most useful data. Then, a variable time slot is specified to each sensor to minimize the transmission of repetitive and un-useful data. The proposed protocol Data-Based Energy Efficient Clustered Routing Protocol for Wireless Sensors Networks (DCRP was compared with the famous energy efficient LEACH protocol and also with one of the recent energy efficient routing protocols named Position Responsive Routing Protocol (PRRP. DCRP has been used in monitoring the floods in Tabuk area –Saudi Arabia. It shows comparatively better results.

  9. Liver Transplantation for Urea Cycle Disorders: Analysis of the United Network for Organ Sharing Database.

    Science.gov (United States)

    Yu, L; Rayhill, S C; Hsu, E K; Landis, C S

    2015-10-01

    Urea cycle disorders (UCD) are caused by rare inherited defects in the urea cycle enzymes leading to diminished ability to convert ammonia to urea in the liver. The resulting excess of circulating ammonia can lead to central nervous system toxicity and irreversible neurologic damage. Most cases are identified in children. However, UCDs can also be diagnosed in adulthood, and liver transplant is occasionally required. We examined the UNOS database to evaluate outcomes in adult and pediatric patients who underwent liver transplant as treatment for a UCD. We identified 265 pediatric and 13 adult patients who underwent liver transplant for a UCD between 1987 and 2010. The majority (68%) of these patients were transplanted before age 5 years. Ornithine transcarbamylase (OTC) deficiency was the most common UCD in both adults and children who underwent transplant. UCD patients who underwent liver transplant were younger, more likely to be male (67%), had lower pediatric end-stage liver disease/model for end-stage liver disease scores, and were more likely to be Caucasian or Asian compared with all other patients transplanted during the same time period. UCD patients did not have an increased utilization of living donor transplantation in this US cohort. Univariate and multivariate risk factor analyses were performed and did not reveal any significant factors that were predictive of post-transplant death or graft loss. Excellent outcomes were seen in both children and adults with UCDs who underwent transplant with overall 1-, 5-, and 10-year survivals of 93%, 89%, and 87%, respectively. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Patterns of severe injury in pediatric car crash victims: Crash Injury Research Engineering Network database.

    Science.gov (United States)

    Brown, J Kristine; Jing, Yuezhou; Wang, Stewart; Ehrlich, Peter F

    2006-02-01

    Motor vehicle crashes (MVCs) account for 50% of pediatric trauma. Safety improvements are typically tested with child crash dummies using an in vitro model. The Crash Injury Research Engineering Network (CIREN) provides an in vivo validation process. Previous research suggest that children in lateral crashes or front-seat locations have higher Injury Severity Scale scores and lower Glasgow Coma Scale scores than those in frontal-impact crashes. However, specific injury patterns and crash characteristics have not been characterized. Data were collected from the CIREN multidisciplinary crash reconstruction network (10 pediatric trauma centers). Injuries were examined with regard to crash direction (frontal/lateral), restraint use, seat location, and change in velocity at impact (DeltaV). Injuries were limited to Abbreviated Injury Scale (AIS) scores of 3 or higher and included head, thoracic, abdominal, pelvic, spine, and long bone (orthopedic) injuries. Standard age groupings (0-4, 5-9, 10-14, and 15-18 years) were used. Statistical analyses used Fisher's Exact test and multiple logistic regressions. Four hundred seventeen MVCs with 2500 injuries were analyzed (males = 219, females = 198). Controlling for DeltaV and age, children in lateral-impact crashes (n = 232) were significantly more likely to suffer severe injuries to the head and thorax as compared with children in frontal crashes (n = 185), who were more likely to suffer severe spine and orthopedic injuries. Children in a front-seat (n = 236) vs those in a back-seat (n = 169) position had more injuries to the thoracic (27% vs 17%), abdominal (21% vs 13%), pelvic (11% vs 1%), and orthopedic (28% vs 10%) regions (P < .05 for all). Seat belts were protective for pelvic (5% vs 12% unbelted) and orthopedic (15% vs 40%) injuries (odds ratio = 3, P < .01 for both). A reproducible pattern of injury is noted for children involved in lateral-impact crashes characterized by head and chest injuries. The Injury Severity

  11. Fault diagnosis for temperature, flow rate and pressure sensors in VAV systems using wavelet neural network

    Energy Technology Data Exchange (ETDEWEB)

    Du, Zhimin; Jin, Xinqiao; Yang, Yunyu [School of Mechanical Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, Shanghai (China)

    2009-09-15

    Wavelet neural network, the integration of wavelet analysis and neural network, is presented to diagnose the faults of sensors including temperature, flow rate and pressure in variable air volume (VAV) systems to ensure well capacity of energy conservation. Wavelet analysis is used to process the original data collected from the building automation first. With three-level wavelet decomposition, the series of characteristic information representing various operation conditions of the system are obtained. In addition, neural network is developed to diagnose the source of the fault. To improve the diagnosis efficiency, three data groups based on several physical models or balances are classified and constructed. Using the data decomposed by three-level wavelet, the neural network can be well trained and series of convergent networks are obtained. Finally, the new measurements to diagnose are similarly processed by wavelet. And the well-trained convergent neural networks are used to identify the operation condition and isolate the source of the fault. (author)

  12. Temperature estimation of induction machines based on wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Y. Huang

    2018-04-01

    Full Text Available In this paper, a fourth-order Kalman filter (KF algorithm is implemented in the wireless sensor node to estimate the temperatures of the stator winding, the rotor cage and the stator core in the induction machine. Three separate wireless sensor nodes are used as the data acquisition systems for different input signals. Six Hall sensors are used to acquire the three-phase stator currents and voltages of the induction machine. All of them are processed to root mean square (rms in ampere and volt. A rotary encoder is mounted for the rotor speed and Pt-1000 is used for the temperature of the coolant air. The processed signals in the physical unit are transmitted wirelessly to the host wireless sensor node, where the KF is implemented with fixed-point arithmetic in Contiki OS. Time-division multiple access (TDMA is used to make the wireless transmission more stable. Compared to the floating-point implementation, the fixed-point implementation has the same estimation accuracy at only about one-fifth of the computation time. The temperature estimation system can work under any work condition as long as there are currents through the machine. It can also be rebooted for estimation even when wireless transmission has collapsed or packages are missing.

  13. Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

    Science.gov (United States)

    Lu, Thomas; Pham, Timothy; Liao, Jason

    2011-01-01

    This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

  14. Artificial neural networks in prediction of mechanical behavior of concrete at high temperature

    International Nuclear Information System (INIS)

    Mukherjee, A.; Nag Biswas, S.

    1997-01-01

    The behavior of concrete structures that are exposed to extreme thermo-mechanical loading is an issue of great importance in nuclear engineering. The mechanical behavior of concrete at high temperature is non-linear. The properties that regulate its response are highly temperature dependent and extremely complex. In addition, the constituent materials, e.g. aggregates, influence the response significantly. Attempts have been made to trace the stress-strain curve through mathematical models and rheological models. However, it has been difficult to include all the contributing factors in the mathematical model. This paper examines a new programming paradigm, artificial neural networks, for the problem. Implementing a feedforward network and backpropagation algorithm the stress-strain relationship of the material is captured. The neural networks for the prediction of uniaxial behavior of concrete at high temperature has been presented here. The results of the present investigation are very encouraging. (orig.)

  15. Noise analysis method for monitoring the moderator temperature coefficient of pressurized water reactors: Neural network calibration

    International Nuclear Information System (INIS)

    Thomas, J.R. Jr.; Adams, J.T.

    1994-01-01

    A neural network was trained with data for the frequency response function between in-core neutron noise and core-exit thermocouple noise in a pressurized water reactor, with the moderator temperature coefficient (MTC) as target. The trained network was subsequently used to predict the MTC at other points in the same fuel cycle. Results support use of the method for operating pressurized water reactors provided noise data can be accumulated for several fuel cycles to provide a training base

  16. Historical database for estimating flows in a water supply network; Base de datos historica para estimacion de caudales en una red de abastecimiento de agua

    Energy Technology Data Exchange (ETDEWEB)

    Menendez Martinez, A.; Ariel Gomez Gutierrez, A.; Alvarez Ramos, I.; Biscarri Trivino, F. [Universidad de Sevilla (Spain)

    2000-07-01

    Monitoring the flows managed by water supply companies involves processing huge amounts of data. These data also have to correspond to the topology of the network in a way that is consistent with the data collection time. The specific purpose database described in this article was developed to meet such requirements. (Author) 4 refs.

  17. Effects of boosting the supply temperature on pipe dimensions of low-energy district heating networks

    DEFF Research Database (Denmark)

    Tol, Hakan; Svendsen, Svend

    2015-01-01

    This paper presents a method for the dimensioning of the low-energy District Heating (DH) piping networks operating with a control philosophy of supplying heat in low-temperature such as 55 °C in supply and 25°C in return regularly while the supply temperature levels are being boosted in cold...... winter periods. The performance of the existing radiators that were formerly sized with over-dimensions was analyzed, its results being used as input data for the performance evaluation of the piping network of the low-energy DH system operating with the control philosophy in question. The optimization...

  18. The Benefits of Using Dense Temperature Sensor Networks to Monitor Urban Warming

    Science.gov (United States)

    Twine, T. E.; Snyder, P. K.; Kucharik, C. J.; Schatz, J.

    2015-12-01

    Urban heat islands (UHIs) occur when urban and suburban areas experience temperatures that are elevated relative to their rural surroundings because of differences in the fraction of gray and green infrastructure. Studies have shown that communities most at risk for impacts from climate-related disasters (i.e., lower median incomes, higher poverty, lower education, and minorities) tend to live in the hottest areas of cities. Development of adequate climate adaptation tools for cities relies on knowledge of how temperature varies across space and time. Traditionally, a city's urban heat island has been quantified using near-surface air temperature measurements from a few sites. This methodology assumes (1) that the UHI can be characterized by the difference in air temperature from a small number of points, and (2) that these few points represent the urban and rural signatures of the region. This methodology ignores the rich information that could be gained from measurements across the urban to rural transect. This transect could traverse elevations, water bodies, vegetation fraction, and other land surface properties. Two temperature sensor networks were designed and implemented in the Minneapolis-Saint Paul, MN and Madison, WI metropolitan areas beginning in 2011 and 2012, respectively. Both networks use the same model sensor and record temperature every 15 minutes from ~150 sensors. Data from each network has produced new knowledge of how temperature varies diurnally and seasonally across the cities and how the UHI magnitude is influenced by weather phenomena (e.g., wind, snow cover, heat waves) and land surface characteristics such as proximity to inland lakes. However, the two metropolitan areas differ in size, population, structure, and orientation to water bodies. In addition, the sensor networks were established in very different manners. We describe these differences and present lessons learned from the design and ongoing efforts of these two dense networks

  19. Development of a database for the prediction of phases in Pt-Al-Cr-Ru alloys for high-temperature and corrosive environments: Al-Cr-Ru

    International Nuclear Information System (INIS)

    Suess, R.; Watson, A.; Cornish, L.A.; Compton, D.N.

    2009-01-01

    Platinum-based alloys for high-temperature corrosive environments are being developed which have microstructures that are analogous to the γ/γ' microstructure of the nickel-based superalloys. The need for a predictive thermodynamic database for these alloys was identified. Because experimental studies suggested that such a database should be based on Pt-Al-Cr-Ru, the Al-Cr-Ru system is of importance in this research programme. Using the CALPHAD method and Thermo-Calc software, existing binary data were used to optimise a ternary database for Al-Cr-Ru against available experimental ternary data. The database gives good predictions with regards to phase equilibria in the system as well as the nature of the primary solidification phases.

  20. Thermo-economic optimization of secondary distribution network of low temperature district heating network under local conditions of South Korea

    DEFF Research Database (Denmark)

    Park, Byung Sik; Imran, Muhammad; Hoon, Im-Yong

    2017-01-01

    . The corresponding heat loss from secondary network, pumping power and area of domestic hot water heat exchanger unit for each supply temperature and temperature difference for required heating load of the apartment complex are calculated. Results indicate that when supply temperature is decreased from 65 °C to 45...... apartment. The Apartment complex has 15 floors, 4 apartments on each floor and each apartment has heating surface area of 85 m2. The supply temperature of the hot water is reduced from 65 °C to 45 °C and the temperature difference between supply and return line is varied from 18 °C to 27 °C...... °C, area of heat exchanger is increased by 68.2%, pumping power is also increased by 9.8% and heat loss is reduced by 15.6%. These results correspond to a temperature difference of 20 °C, the standard temperature difference in South Korea residential heating system. Economic assessment...

  1. Monitoring and Modeling Temperature Variations Inside Silage Stack Using Novel Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Green, Ole; Shahrak Nadimi, Esmaeil; Blanes-Vidal, Victoria

    2009-01-01

    the sensor nodes were successfully delivered to the gateway. The reliable performance of the network confirmed the correct choice of network characteristics (i.e., frequency range of 433 MHz, a handshaking communication protocol and 10 mW transmission power). The designed sensor housings were capable......Abstract: By monitoring silage temperature at different locations inside silage stacks, it is possible to detect any significant increases in temperature occurring during silage decomposition. The objectives of this study were: (1) to develop novel noninvasive wireless sensor nodes for measuring...... the temperature inside silage stacks; (2) to design a suitable sensor protection housing that prevents physical and chemical damage to the sensor; and (3) to mathematically model temperature variations inside a silage stack, using system identification techniques. The designed wireless nodes were used to monitor...

  2. Monitoring and modeling temperature variations inside silage stacks using novel wireless sensor networks

    DEFF Research Database (Denmark)

    Green, O.; Nadimi, E.S.; Blanes-Vidal, V.

    2009-01-01

    the sensor nodes were successfully delivered to the gateway. The reliable performance of the network confirmed the correct choice of network characteristics (i.e., frequency range of 433 MHz, a handshaking communication protocol, and 10 mW transmission power). The designed sensor housings were capable......By monitoring silage temperature at different locations inside silage stacks, it is possible to detect any significant increases in temperature occurring during silage decomposition. The objectives of this study were: (1) to develop novel noninvasive wireless sensor nodes for measuring...... the temperature inside silage stacks; (2) to design a suitable sensor protection housing that prevents physical and chemical damage to the sensor: and (3) to mathematically model temperature variations inside a silage stack, using system identification techniques. The designed wireless nodes were used to monitor...

  3. Glass Transition Temperature Measurement for Undercured Cyanate Ester Networks: Challenges, Tips, and Tricks (Briefing Charts)

    Science.gov (United States)

    2014-01-29

    DISTRIBUTION A: Approved for public release; distribution is unlimited. Thermosetting Polymers Have a TG Envelope – Not Just a TG 4 • The glass transition...glass transition temperature of a thermosetting polymer can vary over a wide range of temperatures depending on how the polymer is processed • A... thermosetting polymer with only one kind of network formation and negligible side reactions, the conversion may be determined at every point in the scan. • By

  4. Coordinating Mobile Databases: A System Demonstration

    OpenAIRE

    Zaihrayeu, Ilya; Giunchiglia, Fausto

    2004-01-01

    In this paper we present the Peer Database Management System (PDBMS). This system runs on top of the standard database management system, and it allows it to connect its database with other (peer) databases on the network. A particularity of our solution is that PDBMS allows for conventional database technology to be effectively operational in mobile settings. We think of database mobility as a database network, where databases appear and disappear spontaneously and their network access point...

  5. Development and Implementation of a Segment/Junction Box Level Database for the ITS Fiber Optic Conduit Network

    Science.gov (United States)

    2012-03-01

    This project initiated the development of a computerized database of ITS facilities, including conduits, junction : boxes, cameras, connections, etc. The current system consists of a database of conduit sections of various lengths. : Over the length ...

  6. Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databases

    Science.gov (United States)

    Malshe, M.; Raff, L. M.; Hagan, M.; Bukkapatnam, S.; Komanduri, R.

    2010-05-01

    The variation in the fitting accuracy of neural networks (NNs) when used to fit databases comprising potential energies obtained from ab initio electronic structure calculations is investigated as a function of the number and nature of the elements employed in the input vector to the NN. Ab initio databases for H2O2, HONO, Si5, and H2CCHBr were employed in the investigations. These systems were chosen so as to include four-, five-, and six-body systems containing first, second, third, and fourth row elements with a wide variety of chemical bonding and whose conformations cover a wide range of structures that occur under high-energy machining conditions and in chemical reactions involving cis-trans isomerizations, six different types of two-center bond ruptures, and two different three-center dissociation reactions. The ab initio databases for these systems were obtained using density functional theory/B3LYP, MP2, and MP4 methods with extended basis sets. A total of 31 input vectors were investigated. In each case, the elements of the input vector were chosen from interatomic distances, inverse powers of the interatomic distance, three-body angles, and dihedral angles. Both redundant and nonredundant input vectors were investigated. The results show that among all the input vectors investigated, the set employed in the Z-matrix specification of the molecular configurations in the electronic structure calculations gave the lowest NN fitting accuracy for both Si5 and vinyl bromide. The underlying reason for this result appears to be the discontinuity present in the dihedral angle for planar geometries. The use of trigometric functions of the angles as input elements produced significantly improved fitting accuracy as this choice eliminates the discontinuity. The most accurate fitting was obtained when the elements of the input vector were taken to have the form Rij-n, where the Rij are the interatomic distances. When the Levenberg-Marquardt procedure was modified

  7. Intelligent Data Transfer for Multiple Sensor Networks over a Broad Temperature Range

    Science.gov (United States)

    Krasowski, Michael (Inventor)

    2018-01-01

    A sensor network may be configured to operate in extreme temperature environments. A sensor may be configured to generate a frequency carrier, and transmit the frequency carrier to a node. The node may be configured to amplitude modulate the frequency carrier, and transmit the amplitude modulated frequency carrier to a receiver.

  8. Retrieving Single Scattering Albedos and Temperatures from CRISM Hyperspectral Data Using Neural Networks

    Science.gov (United States)

    He, L.; Arvidson, R. E.; O'Sullivan, J. A.

    2018-04-01

    We use a neural network (NN) approach to simultaneously retrieve surface single scattering albedos and temperature maps for CRISM data from 1.40 to 3.85 µm. It approximates the inverse of DISORT which simulates solar and emission radiative streams.

  9. Design of a low temperature district heating network with supply recirculation

    DEFF Research Database (Denmark)

    Li, Hongwei; Dalla Rosa, Alessandro; Svendsen, Svend

    2010-01-01

    The focus on continuing improving building energy efficiency and reducing building energy consumption brings the key impetus for the development of the new generation district heating (DH) system. In the new generation DH network, the supply and return temperature are designed low in order to sig...... calculates the heat loss in the twin pipe as that in the single pipe. The influence of this simplification on the supply/return water temperature prediction was analyzed by solving the coupled differential energy equations.......-pass system starts to function. The aim of this paper is to investigate the influence of by-pass water on the network return temperature and introduce the concept of supply water recirculation into the network design so that the traditional by-pass system can be avoided. Instead of mixing the by-pass water......The focus on continuing improving building energy efficiency and reducing building energy consumption brings the key impetus for the development of the new generation district heating (DH) system. In the new generation DH network, the supply and return temperature are designed low in order...

  10. An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network.

    Science.gov (United States)

    Petropoulos, George P; McCalmont, Jon P

    2017-06-23

    This paper describes a soil moisture dataset that has been collecting ground measurements of soil moisture, soil temperature and related parameters for west Wales, United Kingdom. Already acquired in situ data have been archived to the autonomous Wales Soil Moisture Network (WSMN) since its foundation in July 2011. The sites from which measurements are being collected represent a range of conditions typical of the Welsh environment, with climate ranging from oceanic to temperate and a range of the most typical land use/cover types found in Wales. At present, WSMN consists of a total of nine monitoring sites across the area with a concentration of sites in three sub-areas around the region of Aberystwyth located in Mid-Wales. The dataset of composed of 0-5 (or 0-10) cm soil moisture, soil temperature, precipitation, and other ancillary data. WSMN data are provided openly to the public via the International Soil Moisture Network (ISMN) platform. At present, WSMN is also rapidly expanding thanks to funding obtained recently which allows more monitoring sites to be added to the network to the wider community interested in using its data.

  11. Comparing various artificial neural network types for water temperature prediction in rivers

    Science.gov (United States)

    Piotrowski, Adam P.; Napiorkowski, Maciej J.; Napiorkowski, Jaroslaw J.; Osuch, Marzena

    2015-10-01

    A number of methods have been proposed for the prediction of streamwater temperature based on various meteorological and hydrological variables. The present study shows a comparison of few types of data-driven neural networks (multi-layer perceptron, product-units, adaptive-network-based fuzzy inference systems and wavelet neural networks) and nearest neighbour approach for short time streamwater temperature predictions in two natural catchments (mountainous and lowland) located in temperate climate zone, with snowy winters and hot summers. To allow wide applicability of such models, autoregressive inputs are not used and only easily available measurements are considered. Each neural network type is calibrated independently 100 times and the mean, median and standard deviation of the results are used for the comparison. Finally, the ensemble aggregation approach is tested. The results show that simple and popular multi-layer perceptron neural networks are in most cases not outperformed by more complex and advanced models. The choice of neural network is dependent on the way the models are compared. This may be a warning for anyone who wish to promote own models, that their superiority should be verified in different ways. The best results are obtained when mean, maximum and minimum daily air temperatures from the previous days are used as inputs, together with the current runoff and declination of the Sun from two recent days. The ensemble aggregation approach allows reducing the mean square error up to several percent, depending on the case, and noticeably diminishes differences in modelling performance obtained by various neural network types.

  12. Estimation of dew point temperature using neuro-fuzzy and neural network techniques

    Science.gov (United States)

    Kisi, Ozgur; Kim, Sungwon; Shiri, Jalal

    2013-11-01

    This study investigates the ability of two different artificial neural network (ANN) models, generalized regression neural networks model (GRNNM) and Kohonen self-organizing feature maps neural networks model (KSOFM), and two different adaptive neural fuzzy inference system (ANFIS) models, ANFIS model with sub-clustering identification (ANFIS-SC) and ANFIS model with grid partitioning identification (ANFIS-GP), for estimating daily dew point temperature. The climatic data that consisted of 8 years of daily records of air temperature, sunshine hours, wind speed, saturation vapor pressure, relative humidity, and dew point temperature from three weather stations, Daego, Pohang, and Ulsan, in South Korea were used in the study. The estimates of ANN and ANFIS models were compared according to the three different statistics, root mean square errors, mean absolute errors, and determination coefficient. Comparison results revealed that the ANFIS-SC, ANFIS-GP, and GRNNM models showed almost the same accuracy and they performed better than the KSOFM model. Results also indicated that the sunshine hours, wind speed, and saturation vapor pressure have little effect on dew point temperature. It was found that the dew point temperature could be successfully estimated by using T mean and R H variables.

  13. A soil moisture and temperature network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, Niels; Jensen, K. H.

    2011-01-01

    The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data globally, and thus product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and temperature network of Decagon ECH2O 5TE...... SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes...... representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature...

  14. Children's Culture Database (CCD)

    DEFF Research Database (Denmark)

    Wanting, Birgit

    a Dialogue inspired database with documentation, network (individual and institutional profiles) and current news , paper presented at the research seminar: Electronic access to fiction, Copenhagen, November 11-13, 1996......a Dialogue inspired database with documentation, network (individual and institutional profiles) and current news , paper presented at the research seminar: Electronic access to fiction, Copenhagen, November 11-13, 1996...

  15. The influence of cold temperature on cellular excitability of hippocampal networks.

    Science.gov (United States)

    de la Peña, Elvira; Mälkiä, Annika; Vara, Hugo; Caires, Rebeca; Ballesta, Juan J; Belmonte, Carlos; Viana, Felix

    2012-01-01

    The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K(2P)), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K(2P) channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity.

  16. Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

    Science.gov (United States)

    Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

    2017-01-01

    Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.

  17. Foreground removal from WMAP 5 yr temperature maps using an MLP neural network

    Science.gov (United States)

    Nørgaard-Nielsen, H. U.

    2010-09-01

    Aims: One of the main obstacles for extracting the cosmic microwave background (CMB) signal from observations in the mm/sub-mm range is the foreground contamination by emission from Galactic component: mainly synchrotron, free-free, and thermal dust emission. The statistical nature of the intrinsic CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. Methods: The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5 yr temperature data without using any auxiliary data. Results: A simple multilayer perceptron neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also, the systematic errors, i.e. errors correlated with the Galactic foregrounds, are very small. Conclusions: With these results the neural network method is well prepared for dealing with the high - quality CMB data from the ESA Planck Surveyor satellite. unknown author type, collab

  18. Bayesian neural network modeling of tree-ring temperature variability record from the Western Himalayas

    Directory of Open Access Journals (Sweden)

    R. K. Tiwari

    2011-08-01

    Full Text Available A novel technique based on the Bayesian neural network (BNN theory is developed and employed to model the temperature variation record from the Western Himalayas. In order to estimate an a posteriori probability function, the BNN is trained with the Hybrid Monte Carlo (HMC/Markov Chain Monte Carlo (MCMC simulations algorithm. The efficacy of the new algorithm is tested on the well known chaotic, first order autoregressive (AR and random models and then applied to model the temperature variation record decoded from the tree-ring widths of the Western Himalayas for the period spanning over 1226–2000 AD. For modeling the actual tree-ring temperature data, optimum network parameters are chosen appropriately and then cross-validation test is performed to ensure the generalization skill of the network on the new data set. Finally, prediction result based on the BNN model is compared with the conventional artificial neural network (ANN and the AR linear models results. The comparative results show that the BNN based analysis makes better prediction than the ANN and the AR models. The new BNN modeling approach provides a viable tool for climate studies and could also be exploited for modeling other kinds of environmental data.

  19. Foreground removal from Planck Sky Model temperature maps using a MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik; Hebert, K.

    2009-01-01

    with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them...... in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80% of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors....

  20. Application of artificial neural networks in fault diagnosis for 10MW high-temperature gas-cooled reactor

    International Nuclear Information System (INIS)

    Li Hui; Wang Ruipian; Hu Shouyin

    2003-01-01

    This paper makes researches on 10 MW High-Temperature Gas-Cooled Reactor fault diagnosis system using Artificial Neural Network, and uses the tendency value and real value of the data under the accidents to train and test two BP networks respectively. The final diagnostic result is the combination of the results of the two networks. The compound system can enhance the accuracy and adaptability of the diagnosis compared to the single network system

  1. rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

    Science.gov (United States)

    Guo, Liyuan; Wang, Jing

    2018-01-04

    Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Room temperature synthesis of heptazine-based microporous polymer networks as photocatalysts for hydrogen evolution.

    Science.gov (United States)

    Kailasam, Kamalakannan; Schmidt, Johannes; Bildirir, Hakan; Zhang, Guigang; Blechert, Siegfried; Wang, Xinchen; Thomas, Arne

    2013-06-25

    Two emerging material classes are combined in this work, namely polymeric carbon nitrides and microporous polymer networks. The former, polymeric carbon nitrides, are composed of amine-bridged heptazine moieties and showed interesting performance as a metal-free photocatalyst. These materials have, however, to be prepared at high temperatures, making control of their chemical structure difficult. The latter, microporous polymer networks have received increasing interest due to their high surface area, giving rise to interesting applications in gas storage or catalysis. Here, the central building block of carbon nitrides, a functionalized heptazine as monomer, and tecton are used to create microporous polymer networks. The resulting heptazine-based microporous polymers show high porosity, while their chemical structure resembles the ones of carbon nitrides. The polymers show activity for the photocatalytic production of hydrogen from water, even under visible light illumination. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Efficient room temperature hydrogen sensor based on UV-activated ZnO nano-network

    Science.gov (United States)

    Kumar, Mohit; Kumar, Rahul; Rajamani, Saravanan; Ranwa, Sapana; Fanetti, Mattia; Valant, Matjaz; Kumar, Mahesh

    2017-09-01

    Room temperature hydrogen sensors were fabricated from Au embedded ZnO nano-networks using a 30 mW GaN ultraviolet LED. The Au-decorated ZnO nano-networks were deposited on a SiO2/Si substrate by a chemical vapour deposition process. X-ray diffraction (XRD) spectrum analysis revealed a hexagonal wurtzite structure of ZnO and presence of Au. The ZnO nanoparticles were interconnected, forming nano-network structures. Au nanoparticles were uniformly distributed on ZnO surfaces, as confirmed by FESEM imaging. Interdigitated electrodes (IDEs) were fabricated on the ZnO nano-networks using optical lithography. Sensor performances were measured with and without UV illumination, at room temperate, with concentrations of hydrogen varying from 5 ppm to 1%. The sensor response was found to be ˜21.5% under UV illumination and 0% without UV at room temperature for low hydrogen concentration of 5 ppm. The UV-photoactivated mode enhanced the adsorption of photo-induced O- and O2- ions, and the d-band electron transition from the Au nanoparticles to ZnO—which increased the chemisorbed reaction between hydrogen and oxygen. The sensor response was also measured at 150 °C (without UV illumination) and found to be ˜18% at 5 ppm. Energy efficient low cost hydrogen sensors can be designed and fabricated with the combination of GaN UV LEDs and ZnO nanostructures.

  4. Foreground removal from CMB temperature maps using an MLP neural network

    Science.gov (United States)

    Nørgaard-Nielsen, H. U.; Jørgensen, H. E.

    2008-12-01

    One of the main obstacles for extracting the Cosmic Microwave Background (CMB) signal from observations in the mm-submm range is the foreground contamination by emission from Galactic components: mainly synchrotron, free-free and thermal dust emission. Due to the statistical nature of the intrinsic CMB signal it is essential to minimize the systematic errors in the CMB temperature determinations. Following the available knowledge of the spectral behavior of the Galactic foregrounds simple power law-like spectra have been assumed. The feasibility of using a simple neural network for extracting the CMB temperature signal from the combined signal CMB and the foregrounds has been investigated. As a specific example, we have analysed simulated data, as expected from the ESA Planck CMB mission. A simple multilayer perceptron neural network with 2 hidden layers can provide temperature estimates over more than 80 per cent of the sky that are to a high degree uncorrelated with the foreground signals. A single network will be able to cover the dynamic range of the Planck noise level over the entire sky.

  5. Modeling and Prediction of Coal Ash Fusion Temperature based on BP Neural Network

    Directory of Open Access Journals (Sweden)

    Miao Suzhen

    2016-01-01

    Full Text Available Coal ash is the residual generated from combustion of coal. The ash fusion temperature (AFT of coal gives detail information on the suitability of a coal source for gasification procedures, and specifically to which extent ash agglomeration or clinkering is likely to occur within the gasifier. To investigate the contribution of oxides in coal ash to AFT, data of coal ash chemical compositions and Softening Temperature (ST in different regions of China were collected in this work and a BP neural network model was established by XD-APC PLATFORM. In the BP model, the inputs were the ash compositions and the output was the ST. In addition, the ash fusion temperature prediction model was obtained by industrial data and the model was generalized by different industrial data. Compared to empirical formulas, the BP neural network obtained better results. By different tests, the best result and the best configurations for the model were obtained: hidden layer nodes of the BP network was setted as three, the component contents (SiO2, Al2O3, Fe2O3, CaO, MgO were used as inputs and ST was used as output of the model.

  6. Investigating the Potential Impacts of Energy Production in the Marcellus Shale Region Using the Shale Network Database and CUAHSI-Supported Data Tools

    Science.gov (United States)

    Brazil, L.

    2017-12-01

    The Shale Network's extensive database of water quality observations enables educational experiences about the potential impacts of resource extraction with real data. Through open source tools that are developed and maintained by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), researchers, educators, and citizens can access and analyze the very same data that the Shale Network team has used in peer-reviewed publications about the potential impacts of hydraulic fracturing on water. The development of the Shale Network database has been made possible through collection efforts led by an academic team and involving numerous individuals from government agencies, citizen science organizations, and private industry. Thus far, CUAHSI-supported data tools have been used to engage high school students, university undergraduate and graduate students, as well as citizens so that all can discover how energy production impacts the Marcellus Shale region, which includes Pennsylvania and other nearby states. This presentation will describe these data tools, how the Shale Network has used them in developing educational material, and the resources available to learn more.

  7. Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

    Science.gov (United States)

    Voss, Frank; Maule, Alec

    2013-01-01

    A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year

  8. A regional neural network model for predicting mean daily river water temperature

    Science.gov (United States)

    Wagner, Tyler; DeWeber, Jefferson Tyrell

    2014-01-01

    Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

  9. A KINETIC DATABASE FOR ASTROCHEMISTRY (KIDA)

    International Nuclear Information System (INIS)

    Wakelam, V.; Pavone, B.; Hébrard, E.; Hersant, F.; Herbst, E.; Loison, J.-C.; Chandrasekaran, V.; Bergeat, A.; Smith, I. W. M.; Adams, N. G.; Bacchus-Montabonel, M.-C.; Béroff, K.; Bierbaum, V. M.; Chabot, M.; Dalgarno, A.; Van Dishoeck, E. F.; Faure, A.; Geppert, W. D.; Gerlich, D.; Galli, D.

    2012-01-01

    We present a novel chemical database for gas-phase astrochemistry. Named the KInetic Database for Astrochemistry (KIDA), this database consists of gas-phase reactions with rate coefficients and uncertainties that will be vetted to the greatest extent possible. Submissions of measured and calculated rate coefficients are welcome, and will be studied by experts before inclusion into the database. Besides providing kinetic information for the interstellar medium, KIDA is planned to contain such data for planetary atmospheres and for circumstellar envelopes. Each year, a subset of the reactions in the database (kida.uva) will be provided as a network for the simulation of the chemistry of dense interstellar clouds with temperatures between 10 K and 300 K. We also provide a code, named Nahoon, to study the time-dependent gas-phase chemistry of zero-dimensional and one-dimensional interstellar sources.

  10. An efficient transmission power control scheme for temperature variation in wireless sensor networks.

    Science.gov (United States)

    Lee, Jungwook; Chung, Kwangsue

    2011-01-01

    Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption.

  11. An Efficient Transmission Power Control Scheme for Temperature Variation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jungwook Lee

    2011-03-01

    Full Text Available Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption.

  12. DMPD: Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory disease. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 18031251 Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory...l) (.csml) Show Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory dis...utrophilic inflammation inrespiratory disease. Authors Sabroe I, Whyte MK. Publication Biochem Soc Trans. 20

  13. [Establishment of the database of the 3D facial models for the plastic surgery based on network].

    Science.gov (United States)

    Liu, Zhe; Zhang, Hai-Lin; Zhang, Zheng-Guo; Qiao, Qun

    2008-07-01

    To collect the three-dimensional (3D) facial data of 30 facial deformity patients by the 3D scanner and establish a professional database based on Internet. It can be helpful for the clinical intervention. The primitive point data of face topography were collected by the 3D scanner. Then the 3D point cloud was edited by reverse engineering software to reconstruct the 3D model of the face. The database system was divided into three parts, including basic information, disease information and surgery information. The programming language of the web system is Java. The linkages between every table of the database are credibility. The query operation and the data mining are convenient. The users can visit the database via the Internet and use the image analysis system to observe the 3D facial models interactively. In this paper we presented a database and a web system adapt to the plastic surgery of human face. It can be used both in clinic and in basic research.

  14. Neurovascular Network Explorer 1.0: a database of 2-photon single-vessel diameter measurements with MATLAB(®) graphical user interface.

    Science.gov (United States)

    Sridhar, Vishnu B; Tian, Peifang; Dale, Anders M; Devor, Anna; Saisan, Payam A

    2014-01-01

    We present a database client software-Neurovascular Network Explorer 1.0 (NNE 1.0)-that uses MATLAB(®) based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.

  15. Healable, Transparent, Room-Temperature Electronic Sensors Based on Carbon Nanotube Network-Coated Polyelectrolyte Multilayers.

    Science.gov (United States)

    Bai, Shouli; Sun, Chaozheng; Yan, Hong; Sun, Xiaoming; Zhang, Han; Luo, Liang; Lei, Xiaodong; Wan, Pengbo; Chen, Xiaodong

    2015-11-18

    Transparent and conductive film based electronics have attracted substantial research interest in various wearable and integrated display devices in recent years. The breakdown of transparent electronics prompts the development of transparent electronics integrated with healability. A healable transparent chemical gas sensor device is assembled from layer-by-layer-assembled transparent healable polyelectrolyte multilayer films by developing effective methods to cast transparent carbon nanotube (CNT) networks on healable substrates. The healable CNT network-containing film with transparency and superior network structures on self-healing substrate is obtained by the lateral movement of the underlying self-healing layer to bring the separated areas of the CNT layer back into contact. The as-prepared healable transparent film is assembled into healable transparent chemical gas sensor device for flexible, healable gas sensing at room temperature, due to the 1D confined network structure, relatively high carrier mobility, and large surface-to-volume ratio. The healable transparent chemical gas sensor demonstrates excellent sensing performance, robust healability, reliable flexibility, and good transparency, providing promising opportunities for developing flexible, healable transparent optoelectronic devices with the reduced raw material consumption, decreased maintenance costs, improved lifetime, and robust functional reliability. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

    Science.gov (United States)

    Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

    2007-07-01

    An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

  17. Interpenetrating metal-organic and inorganic 3D networks: a computer-aided systematic investigation. Part II [1]. Analysis of the Inorganic Crystal Structure Database (ICSD)

    International Nuclear Information System (INIS)

    Baburin, I.A.; Blatov, V.A.; Carlucci, L.; Ciani, G.; Proserpio, D.M.

    2005-01-01

    Interpenetration in metal-organic and inorganic networks has been investigated by a systematic analysis of the crystallographic structural databases. We have used a version of TOPOS (a package for multipurpose crystallochemical analysis) adapted for searching for interpenetration and based on the concept of Voronoi-Dirichlet polyhedra and on the representation of a crystal structure as a reduced finite graph. In this paper, we report comprehensive lists of interpenetrating inorganic 3D structures from the Inorganic Crystal Structure Database (ICSD), inclusive of 144 Collection Codes for equivalent interpenetrating nets, analyzed on the basis of their topologies. Distinct Classes, corresponding to the different modes in which individual identical motifs can interpenetrate, have been attributed to the entangled structures. Interpenetrating nets of different nature as well as interpenetrating H-bonded nets were also examined

  18. HydroClim: a Continental-Scale Database of Contemporary and Future Streamflow and Stream Temperature Estimates for Aquatic Ecosystem Studies

    Science.gov (United States)

    Knouft, J.; Ficklin, D. L.; Bart, H. L.; Rios, N. E.

    2017-12-01

    Streamflow and water temperature are primary factors influencing the traits, distribution, and diversity of freshwater species. Ongoing changes in climate are causing directional alteration of these environmental conditions, which can impact local ecological processes. Accurate estimation of these variables is critical for predicting the responses of species to ongoing changes in freshwater habitat, yet ecologically relevant high-resolution data describing variation in streamflow and water temperature across North America are not available. Considering the vast amount of web-accessible freshwater biodiversity data, development and application of appropriate hydrologic data are critical to the advancement of our understanding of freshwater systems. To address this issue, we are developing the "HydroClim" database, which will provide web-accessible (www.hydroclim.org) historical and projected monthly streamflow and water temperature data for stream sections in all major watersheds across the United States and Canada from 1950-2099. These data will also be integrated with FishNet 2 (www.fishnet2.net), an online biodiversity database that provides open access to over 2 million localities of freshwater fish species in the United States and Canada, thus allowing for the characterization of the habitat requirements of freshwater species across this region. HydroClim should provide a vast array of opportunities for a greater understanding of water resources as well as information for the conservation of freshwater biodiversity in the United States and Canada in the coming century.

  19. Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature.

    Science.gov (United States)

    Bhandari, Siddhartha; Bergmann, Neil; Jurdak, Raja; Kusy, Branislav

    2017-05-26

    Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2 °C and forecasting RMSE less than 1 °C.

  20. A fuzzy neural network model to forecast the percent cloud coverage and cloud top temperature maps

    Directory of Open Access Journals (Sweden)

    Y. Tulunay

    2008-12-01

    Full Text Available Atmospheric processes are highly nonlinear. A small group at the METU in Ankara has been working on a fuzzy data driven generic model of nonlinear processes. The model developed is called the Middle East Technical University Fuzzy Neural Network Model (METU-FNN-M. The METU-FNN-M consists of a Fuzzy Inference System (METU-FIS, a data driven Neural Network module (METU-FNN of one hidden layer and several neurons, and a mapping module, which employs the Bezier Surface Mapping technique. In this paper, the percent cloud coverage (%CC and cloud top temperatures (CTT are forecast one month ahead of time at 96 grid locations. The probable influence of cosmic rays and sunspot numbers on cloudiness is considered by using the METU-FNN-M.

  1. Foreground removal from Planck Sky Model temperature maps using a MLP neural network

    Science.gov (United States)

    Nørgaard-Nielsen, H. U.; Hebert, K.

    2009-08-01

    Unfortunately, the Cosmic Microwave Background (CMB) radiation is contaminated by emission originating in the Milky Way (synchrotron, free-free and dust emission). Since the cosmological information is statistically in nature, it is essential to remove this foreground emission and leave the CMB with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80 % of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors.

  2. Using Wireless Sensor Networks to Achieve Intelligent Monitoring for High-Temperature Gas-Cooled Reactor

    Directory of Open Access Journals (Sweden)

    Jianghai Li

    2017-01-01

    Full Text Available High-temperature gas-cooled reactors (HTGR can incorporate wireless sensor network (WSN technology to improve safety and economic competitiveness. WSN has great potential in monitoring the equipment and processes within nuclear power plants (NPPs. This technology not only reduces the cost of regular monitoring but also enables intelligent monitoring. In intelligent monitoring, large sets of heterogeneous data collected by the WSN can be used to optimize the operation and maintenance of the HTGR. In this paper, WSN-based intelligent monitoring schemes that are specific for applications of HTGR are proposed. Three major concerns regarding wireless technology in HTGR are addressed: wireless devices interference, cybersecurity of wireless networks, and wireless standards selected for wireless platform. To process nonlinear and non-Gaussian data obtained by WSN for fault diagnosis, novel algorithms combining Kernel Entropy Component Analysis (KECA and support vector machine (SVM are developed.

  3. Response surface and neural network based predictive models of cutting temperature in hard turning

    Directory of Open Access Journals (Sweden)

    Mozammel Mia

    2016-11-01

    Full Text Available The present study aimed to develop the predictive models of average tool-workpiece interface temperature in hard turning of AISI 1060 steels by coated carbide insert. The Response Surface Methodology (RSM and Artificial Neural Network (ANN were employed to predict the temperature in respect of cutting speed, feed rate and material hardness. The number and orientation of the experimental trials, conducted in both dry and high pressure coolant (HPC environments, were planned using full factorial design. The temperature was measured by using the tool-work thermocouple. In RSM model, two quadratic equations of temperature were derived from experimental data. The analysis of variance (ANOVA and mean absolute percentage error (MAPE were performed to suffice the adequacy of the models. In ANN model, 80% data were used to train and 20% data were employed for testing. Like RSM, herein, the error analysis was also conducted. The accuracy of the RSM and ANN model was found to be ⩾99%. The ANN models exhibit an error of ∼5% MAE for testing data. The regression coefficient was found to be greater than 99.9% for both dry and HPC. Both these models are acceptable, although the ANN model demonstrated a higher accuracy. These models, if employed, are expected to provide a better control of cutting temperature in turning of hardened steel.

  4. Artificial Neural Networks for differential diagnosis of breast lesions in MR-Mammography: A systematic approach addressing the influence of network architecture on diagnostic performance using a large clinical database

    International Nuclear Information System (INIS)

    Dietzel, Matthias; Baltzer, Pascal A.T.; Dietzel, Andreas; Zoubi, Ramy; Gröschel, Tobias; Burmeister, Hartmut P.; Bogdan, Martin; Kaiser, Werner A.

    2012-01-01

    Rationale and objectives: Differential diagnosis of lesions in MR-Mammography (MRM) remains a complex task. The aim of this MRM study was to design and to test robustness of Artificial Neural Network architectures to predict malignancy using a large clinical database. Materials and methods: For this IRB-approved investigation standardized protocols and study design were applied (T1w-FLASH; 0.1 mmol/kgBW Gd-DTPA; T2w-TSE; histological verification after MRM). All lesions were evaluated by two experienced (>500 MRM) radiologists in consensus. In every lesion, 18 previously published descriptors were assessed and documented in the database. An Artificial Neural Network (ANN) was developed to process this database (The-MathWorks/Inc., feed-forward-architecture/resilient back-propagation-algorithm). All 18 descriptors were set as input variables, whereas histological results (malignant vs. benign) was defined as classification variable. Initially, the ANN was optimized in terms of “Training Epochs” (TE), “Hidden Layers” (HL), “Learning Rate” (LR) and “Neurons” (N). Robustness of the ANN was addressed by repeated evaluation cycles (n: 9) with receiver operating characteristics (ROC) analysis of the results applying 4-fold Cross Validation. The best network architecture was identified comparing the corresponding Area under the ROC curve (AUC). Results: Histopathology revealed 436 benign and 648 malignant lesions. Enhancing the level of complexity could not increase diagnostic accuracy of the network (P: n.s.). The optimized ANN architecture (TE: 20, HL: 1, N: 5, LR: 1.2) was accurate (mean-AUC 0.888; P: <0.001) and robust (CI: 0.885–0.892; range: 0.880–0.898). Conclusion: The optimized neural network showed robust performance and high diagnostic accuracy for prediction of malignancy on unknown data.

  5. Artificial Neural Networks for differential diagnosis of breast lesions in MR-Mammography: a systematic approach addressing the influence of network architecture on diagnostic performance using a large clinical database.

    Science.gov (United States)

    Dietzel, Matthias; Baltzer, Pascal A T; Dietzel, Andreas; Zoubi, Ramy; Gröschel, Tobias; Burmeister, Hartmut P; Bogdan, Martin; Kaiser, Werner A

    2012-07-01

    Differential diagnosis of lesions in MR-Mammography (MRM) remains a complex task. The aim of this MRM study was to design and to test robustness of Artificial Neural Network architectures to predict malignancy using a large clinical database. For this IRB-approved investigation standardized protocols and study design were applied (T1w-FLASH; 0.1 mmol/kgBW Gd-DTPA; T2w-TSE; histological verification after MRM). All lesions were evaluated by two experienced (>500 MRM) radiologists in consensus. In every lesion, 18 previously published descriptors were assessed and documented in the database. An Artificial Neural Network (ANN) was developed to process this database (The-MathWorks/Inc., feed-forward-architecture/resilient back-propagation-algorithm). All 18 descriptors were set as input variables, whereas histological results (malignant vs. benign) was defined as classification variable. Initially, the ANN was optimized in terms of "Training Epochs" (TE), "Hidden Layers" (HL), "Learning Rate" (LR) and "Neurons" (N). Robustness of the ANN was addressed by repeated evaluation cycles (n: 9) with receiver operating characteristics (ROC) analysis of the results applying 4-fold Cross Validation. The best network architecture was identified comparing the corresponding Area under the ROC curve (AUC). Histopathology revealed 436 benign and 648 malignant lesions. Enhancing the level of complexity could not increase diagnostic accuracy of the network (P: n.s.). The optimized ANN architecture (TE: 20, HL: 1, N: 5, LR: 1.2) was accurate (mean-AUC 0.888; P: <0.001) and robust (CI: 0.885-0.892; range: 0.880-0.898). The optimized neural network showed robust performance and high diagnostic accuracy for prediction of malignancy on unknown data. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  6. High temperature superconducting material: Bismuth strontium calcium copper oxide. (Latest citations from the Aerospace database). Published Search

    International Nuclear Information System (INIS)

    1993-11-01

    The bibliography contains citations concerning the development, fabrication, and analysis of a high temperature superconducting material based on bismuth-strontium-calcium-copper-oxides (Bi-Sr-Ca-Cu-O). Topics include the physical properties, structural and compositional analysis, magnetic field and pressure effects, and noble metal dopings of Bi-Sr-Ca-Cu-O based systems. The highest transition temperature recorded to date for this material was 120 degrees Kelvin. Fabrication methods and properties of Bi-Sr-Ca-Cu-O films and ceramics are also considered. (Contains 250 citations and includes a subject term index and title list.)

  7. National Transportation Atlas Databases : 2012.

    Science.gov (United States)

    2012-01-01

    The National Transportation Atlas Databases 2012 (NTAD2012) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  8. National Transportation Atlas Databases : 2011.

    Science.gov (United States)

    2011-01-01

    The National Transportation Atlas Databases 2011 (NTAD2011) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  9. National Transportation Atlas Databases : 2009.

    Science.gov (United States)

    2009-01-01

    The National Transportation Atlas Databases 2009 (NTAD2009) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  10. National Transportation Atlas Databases : 2010.

    Science.gov (United States)

    2010-01-01

    The National Transportation Atlas Databases 2010 (NTAD2010) is a set of nationwide geographic databases of transportation facilities, transportation networks, and associated infrastructure. These datasets include spatial information for transportatio...

  11. Combined IR imaging-neural network method for the estimation of internal temperature in cooked chicken meat

    Science.gov (United States)

    Ibarra, Juan G.; Tao, Yang; Xin, Hongwei

    2000-11-01

    A noninvasive method for the estimation of internal temperature in chicken meat immediately following cooking is proposed. The external temperature from IR images was correlated with measured internal temperature through a multilayer neural network. To provide inputs for the network, time series experiments were conducted to obtain simultaneous observations of internal and external temperatures immediately after cooking during the cooling process. An IR camera working at the spectral band of 3.4 to 5.0 micrometers registered external temperature distributions without the interference of close-to-oven environment, while conventional thermocouples registered internal temperatures. For an internal temperature at a given time, simultaneous and lagged external temperature observations were used as the input of the neural network. Based on practical and statistical considerations, a criterion is established to reduce the nodes in the neural network input. The combined method was able to estimate internal temperature for times between 0 and 540 s within a standard error of +/- 1.01 degree(s)C, and within an error of +/- 1.07 degree(s)C for short times after cooking (3 min), with two thermograms at times t and t+30s. The method has great potential for monitoring of doneness of chicken meat in conveyor belt type cooking and can be used as a platform for similar studies in other food products.

  12. A Survey on Temperature-Aware Routing Protocols in Wireless Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sangman Moh

    2013-08-01

    Full Text Available The rapid growth of the elderly population in the world and the rising cost of healthcare impose big issues for healthcare and medical monitoring. A Wireless Body Sensor Network (WBSN is comprised of small sensor nodes attached inside, on or around a human body, the main purpose of which is to monitor the functions and surroundings of the human body. However, the heat generated by the node’s circuitry and antenna could cause damage to the human tissue. Therefore, in designing a routing protocol for WBSNs, it is important to reduce the heat by incorporating temperature into the routing metric. The main contribution of this paper is to survey existing temperature-aware routing protocols that have been proposed for WBSNs. In this paper, we present a brief overview of WBSNs, review the existing routing protocols comparatively and discuss challenging open issues in the design of routing protocols.

  13. Tradeoffs in distributed databases

    OpenAIRE

    Juntunen, R. (Risto)

    2016-01-01

    Abstract In a distributed database data is spread throughout the network into separated nodes with different DBMS systems (Date, 2000). According to CAP-theorem three database properties — consistency, availability and partition tolerance cannot be achieved simultaneously in distributed database systems. Two of these properties can be achieved but not all three at the same time (Brewer, 2000). Since this theorem there has b...

  14. Artificial Neural Network-Based Monitoring of the Fuel Assembly Temperature Sensor and FPGA Implementation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2015-07-01

    Numerous methods have been developed around the world to model the dynamic behavior and detect a faulty operating mode of a temperature sensor. In this context, we present in this study a new method based on the dependence between the fuel assembly temperature profile on control rods positions, and the coolant flow rate in a nuclear reactor. This seems to be possible since the insertion of control rods at different axial positions and variations in flow rate of the reactor coolant results in different produced thermal power in the reactor. This is closely linked to the instant fuel rod temperature profile. In a first step, we selected parameters to be used and confirmed the adequate correlation between the chosen parameters and those to be estimated by the proposed monitoring system. In the next step, we acquired and de-noised the data of corresponding parameters, the qualified data is then used to design and train the artificial neural network. The effective data denoising was done by using the wavelet transform to remove a various kind of artifacts such as inherent noise. With the suitable choice of wavelet level and smoothing method, it was possible for us to remove all the non-required artifacts with a view to verify and analyze the considered signal. In our work, several potential mother wavelet functions (Haar, Daubechies, Bi-orthogonal, Reverse Bi-orthogonal, Discrete Meyer and Symlets) were investigated to find the most similar function with the being processed signals. To implement the proposed monitoring system for the fuel rod temperature sensor (03 wire RTD sensor), we used the Bayesian artificial neural network 'BNN' technique to model the dynamic behavior of the considered sensor, the system correlate the estimated values with the measured for the concretization of the proposed system we propose an FPGA (field programmable gate array) implementation. The monitoring system use the correlation. (authors)

  15. Computer application for database management and networking of service radio physics; Aplicacion informatica para la gestion de bases de datos y conexiones en red de un servicio de radiofisica

    Energy Technology Data Exchange (ETDEWEB)

    Ferrando Sanchez, A.; Cabello Murillo, E.; Diaz Fuentes, R.; Castro Novais, J.; Clemente Gutierrez, F.; Casa de Juan, M. A. de la; Adaimi Hernandez, P.

    2011-07-01

    The databases in the quality control prove to be a powerful tool for recording, management and statistical process control. Developed in a Windows environment and under Access (Microsoft Office) our service implements this philosophy on the centers computer network. A computer that acts as the server provides the database to the treatment units to record quality control measures daily and incidents. To remove shortcuts stop working with data migration, possible use of duplicate and erroneous data loss because of errors in network connections, which are common problems, we proceeded to manage connections and access to databases ease of maintenance and use horn to all service personnel.

  16. Fast Rotational Diffusion of Water Molecules in a 2D Hydrogen Bond Network at Cryogenic Temperatures

    Science.gov (United States)

    Prisk, T. R.; Hoffmann, C.; Kolesnikov, A. I.; Mamontov, E.; Podlesnyak, A. A.; Wang, X.; Kent, P. R. C.; Anovitz, L. M.

    2018-05-01

    Individual water molecules or small clusters of water molecules contained within microporous minerals present an extreme case of confinement where the local structure of hydrogen bond networks are dramatically altered from bulk water. In the zinc silicate hemimorphite, the water molecules form a two-dimensional hydrogen bond network with hydroxyl groups in the crystal framework. Here, we present a combined experimental and theoretical study of the structure and dynamics of water molecules within this network. The water molecules undergo a continuous phase transition in their orientational configuration analogous to a two-dimensional Ising model. The incoherent dynamic structure factor reveals two thermally activated relaxation processes, one on a subpicosecond timescale and another on a 10-100 ps timescale, between 70 and 130 K. The slow process is an in-plane reorientation of the water molecule involving the breaking of hydrogen bonds with a framework that, despite the low temperatures involved, is analogous to rotational diffusion of water molecules in the bulk liquid. The fast process is a localized motion of the water molecule with no apparent analogs among known bulk or confined phases of water.

  17. Network structure and thermal stability study of high temperature seal glass

    Science.gov (United States)

    Lu, K.; Mahapatra, M. K.

    2008-10-01

    High temperature seal glass has stringent requirement on glass thermal stability, which is dictated by glass network structures. In this study, a SrO-La2O3-Al2O3-B2O3-SiO2 based glass system was studied using nuclear magnetic resonance, Raman spectroscopy, and x-ray diffraction for solid oxide cell application purpose. Glass structural unit neighboring environment and local ordering were evaluated. Glass network connectivity as well as silicon and boron glass former coordination were calculated for different B2O3:SiO2 ratios. Thermal stability of the borosilicate glasses was studied after thermal treatment at 850 °C. The study shows that high B2O3 content induces BO4 and SiO4 structural unit ordering, increases glass localized inhomogeneity, decreases glass network connectivity, and causes devitrification. Glass modifiers interact with either silicon- or boron-containing structural units and form different devitrified phases at different B2O3:SiO2 ratios. B2O3-free glass shows the best thermal stability among the studied compositions, remaining stable after thermal treatment for 200 h at 850 °C.

  18. Temperature dependence of the partially localized state in a 2D molecular nanoporous network

    Energy Technology Data Exchange (ETDEWEB)

    Piquero-Zulaica, Ignacio, E-mail: ipiquerozulaica@gmail.com [Centro de Física de Materiales (CSIC/UPV-EHU)—Materials Physics Center, Manuel Lardizabal 5, 20018 San Sebastián (Spain); Nowakowska, Sylwia [Department of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel (Switzerland); Ortega, J. Enrique [Centro de Física de Materiales (CSIC/UPV-EHU)—Materials Physics Center, Manuel Lardizabal 5, 20018 San Sebastián (Spain); Donostia International Physics Center (DIPC), Manuel Lardizabal 4, 20018 San Sebastián (Spain); Departamento Física Aplicada I, Universidad del País Vasco, 20018 San Sebastián (Spain); Stöhr, Meike [Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 4, 9747 AG Groningen (Netherlands); Gade, Lutz H. [Anorganisch-Chemisches Institut, Universität Heidelberg, Im Neuenheimer Feld 270, 69120 Heidelberg (Germany); Jung, Thomas A. [Laboratory for Micro- and Nanotechnology, Paul Scherrer Institute, 5232 Villigen (Switzerland); Lobo-Checa, Jorge, E-mail: jorge.lobo@csic.es [Instituto de Ciencia de Materiales de Aragón (ICMA), CSIC-Universidad de Zaragoza, E-50009 Zaragoza (Spain); Departamento de Física de la Materia Condensada, Universidad de Zaragoza, E-50009 Zaragoza (Spain)

    2017-01-01

    Highlights: • A state of a 2D porous network is demonstrated to originate from the Shockley state. • The temperature evolution of both states is followed by means of ARPES. • Identical energy shifts are observed for both states, proving their common origin. - Abstract: Two-dimensional organic and metal-organic nanoporous networks can scatter surface electrons, leading to their partial localization. Such quantum states are related to intrinsic surface states of the substrate material. We further corroborate this relation by studying the thermally induced energy shifts of the electronic band stemming from coupled quantum states hosted in a metal-organic array formed by a perylene derivative on Cu(111). We observe by angle-resolved photoemission spectroscopy (ARPES), that both, the Shockley and the partially localized states, shift by the same amount to higher binding energies upon decreasing the sample temperature, providing evidence of their common origin. Our experimental approach and results further support the use of surface states for modelling these systems, which are expected to provide new insight into the physics concerning partially confined electronic states: scattering processes, potential barrier strengths, excited state lifetimes or the influence of guest molecules.

  19. Hard-Wired Dopant Networks and the Prediction of High Transition Temperatures in Ceramic Superconductors

    International Nuclear Information System (INIS)

    Phillips, J.C.

    2010-01-01

    The review multiple successes of the discrete hard-wired dopant network model ZZIP, and comment on the equally numerous failures of continuum models, in describing and predicting the properties of ceramic superconductors. The prediction of transition temperatures can be regarded in several ways, either as an exacting test of theory, or as a tool for identifying theoretical rules for defining new homology models. Popular first principle methods for predicting transition temperatures in conventional crystalline superconductors have failed for cuprate HTSC, as have parameterized models based on CuO2 planes (with or without apical oxygen). Following a path suggested by Bayesian probability, it was found that the glassy, self-organized dopant network percolative model is so successful that it defines a new homology class appropriate to ceramic superconductors. The reasons for this success in an exponentially complex (non-polynomial complete, NPC) problem are discussed, and a critical comparison is made with previous polynomial (PC) theories. The predictions are successful for the superfamily of all ceramics, including new non-cuprates based on FeAs in place of CuO2.

  20. Equivalent electrical network model approach applied to a double acting low temperature differential Stirling engine

    International Nuclear Information System (INIS)

    Formosa, Fabien; Badel, Adrien; Lottin, Jacques

    2014-01-01

    Highlights: • An equivalent electrical network modeling of Stirling engine is proposed. • This model is applied to a membrane low temperate double acting Stirling engine. • The operating conditions (self-startup and steady state behavior) are defined. • An experimental engine is presented and tested. • The model is validated against experimental results. - Abstract: This work presents a network model to simulate the periodic behavior of a double acting free piston type Stirling engine. Each component of the engine is considered independently and its equivalent electrical circuit derived. When assembled in a global electrical network, a global model of the engine is established. Its steady behavior can be obtained by the analysis of the transfer function for one phase from the piston to the expansion chamber. It is then possible to simulate the dynamic (steady state stroke and operation frequency) as well as the thermodynamic performances (output power and efficiency) for given mean pressure, heat source and heat sink temperatures. The motion amplitude especially can be determined by the spring-mass properties of the moving parts and the main nonlinear effects which are taken into account in the model. The thermodynamic features of the model have then been validated using the classical isothermal Schmidt analysis for a given stroke. A three-phase low temperature differential double acting free membrane architecture has been built and tested. The experimental results are compared with the model and a satisfactory agreement is obtained. The stroke and operating frequency are predicted with less than 2% error whereas the output power discrepancy is of about 30%. Finally, some optimization routes are suggested to improve the design and maximize the performances aiming at waste heat recovery applications

  1. DMPD: Glucocorticoids and the innate immune system: crosstalk with the toll-likereceptor signaling network. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17576036 Glucocorticoids and the innate immune system: crosstalk with the toll-like...07 May 13. (.png) (.svg) (.html) (.csml) Show Glucocorticoids and the innate immune system: crosstalk with t...nd the innate immune system: crosstalk with the toll-likereceptor signaling network. Authors Chinenov Y, Rog

  2. Relational nuclear databases upon the MSU INP CDFE Web-site and Nuclear Data Centres Network CDFE activities. P7

    International Nuclear Information System (INIS)

    Boboshin, I.N.; Varlamov, V.V.; Ivanov, E.M.; Ivanov, S.V.; Peskov, N.N.; Stepanov, M.E.; Chesnokov, V.V.

    2001-01-01

    This report contains only the short review of the work carried out by the CDFE concerning the IAEA Nuclear Reaction Data Centres Network activities for the period of time from the IAEA Advisory Group Meeting (15-19 May 2000, Obninsk, Russia) till May 2001 and the description of the main results obtained

  3. Artificial neural networks for dynamic monitoring of simulated-operating parameters of high temperature gas cooled engineering test reactor (HTTR)

    International Nuclear Information System (INIS)

    Seker, Serhat; Tuerkcan, Erdinc; Ayaz, Emine; Barutcu, Burak

    2003-01-01

    This paper addresses to the problem of utilisation of the artificial neural networks (ANNs) for detecting anomalies as well as physical parameters of a nuclear power plant during power operation in real time. Three different types of neural network algorithms were used namely, feed-forward neural network (back-propagation, BP) and two types of recurrent neural networks (RNN). The data used in this paper were gathered from the simulation of the power operation of the Japan's High Temperature Engineering Testing Reactor (HTTR). For the wide range of power operation, 56 signals were generated by the reactor dynamic simulation code for several hours of normal power operation at different power ramps between 30 and 100% nominal power. Paper will compare the outcomes of different neural networks and presents the neural network system and the determination of physical parameters from the simulated operating data

  4. Continental-Scale Temperature Reconstructions from the PAGES 2k Network

    Science.gov (United States)

    Kaufman, D. S.

    2012-12-01

    We present a major new synthesis of seven regional temperature reconstructions to elucidate the global pattern of variations and their association with climate-forcing mechanisms over the past two millennia. To coordinate the integration of new and existing data of all proxy types, the Past Global Changes (PAGES) project developed the 2k Network. It comprises nine working groups representing eight continental-scale regions and the oceans. The PAGES 2k Consortium, authoring this paper, presently includes 79 representatives from 25 countries. For this synthesis, each of the PAGES 2k working groups identified the proxy climate records for reconstructing past temperature and associated uncertainty using the data and methodologies that they deemed most appropriate for their region. The datasets are from 973 sites where tree rings, pollen, corals, lake and marine sediment, glacier ice, speleothems, and historical documents record changes in biologically and physically mediated processes that are sensitive to temperature change, among other climatic factors. The proxy records used for this synthesis are available through the NOAA World Data Center for Paleoclimatology. On long time scales, the temperature reconstructions display similarities among regions, and a large part of this common behavior can be explained by known climate forcings. Reconstructed temperatures in all regions show an overall long-term cooling trend until around 1900 C.E., followed by strong warming during the 20th century. On the multi-decadal time scale, we assessed the variability among the temperature reconstructions using principal component (PC) analysis of the standardized decadal mean temperatures over the period of overlap among the reconstructions (1200 to 1980 C.E.). PC1 explains 35% of the total variability and is strongly correlated with temperature reconstructions from the four Northern Hemisphere regions, and with the sum of external forcings including solar, volcanic, and greenhouse

  5. Optimization of Residual Stress of High Temperature Treatment Using Genetic Algorithm and Neural Network

    Directory of Open Access Journals (Sweden)

    M. Susmikanti

    2015-12-01

    Full Text Available In a nuclear industry area, high temperature treatment of materials is a factor which requires special attention. Assessment needs to be conducted on the properties of the materials used, including the strength of the materials. The measurement of material properties under thermal processes may reflect residual stresses. The use of Genetic Algorithm (GA to determine the optimal residual stress is one way to determine the strength of a material. In residual stress modeling with several parameters, it is sometimes difficult to solve for the optimal value through analytical or numerical calculations. Here, GA is an efficient algorithm which can generate the optimal values, both minima and maxima. The purposes of this research are to obtain the optimization of variable in residual stress models using GA and to predict the center of residual stress distribution, using fuzzy neural network (FNN while the artificial neural network (ANN used for modeling. In this work a single-material 316/316L stainless steel bar is modeled. The minimal residual stresses of the material at high temperatures were obtained with GA and analytical calculations. At a temperature of 6500C, the GA optimal residual stress estimation converged at –711.3689 MPa at adistance of 0.002934 mm from center point, whereas the analytical calculation result at that temperature and position is -975.556 MPa . At a temperature of 8500C, the GA result was -969.868 MPa at 0.002757 mm from the center point, while with analytical result was -1061.13 MPa. The difference in residual stress between GA and analytical results at a temperatureof6500C is about 27 %, while at 8500C it is 8.67 %. The distribution of residual stress showed a grouping concentrated around a coordinate of (-76; 76 MPa. The residuals stress model is a degree-two polynomial with coefficients of 50.33, -76.54, and -55.2, respectively, with a standard deviation of 7.874.

  6. Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network.

    Science.gov (United States)

    Sun, Xingming; Yan, Shuangshuang; Wang, Baowei; Xia, Li; Liu, Qi; Zhang, Hui

    2015-07-24

    Air temperature (AT) is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS). Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR). Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE) and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

  7. Air Temperature Error Correction Based on Solar Radiation in an Economical Meteorological Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Xingming Sun

    2015-07-01

    Full Text Available Air temperature (AT is an extremely vital factor in meteorology, agriculture, military, etc., being used for the prediction of weather disasters, such as drought, flood, frost, etc. Many efforts have been made to monitor the temperature of the atmosphere, like automatic weather stations (AWS. Nevertheless, due to the high cost of specialized AT sensors, they cannot be deployed within a large spatial density. A novel method named the meteorology wireless sensor network relying on a sensing node has been proposed for the purpose of reducing the cost of AT monitoring. However, the temperature sensor on the sensing node can be easily influenced by environmental factors. Previous research has confirmed that there is a close relation between AT and solar radiation (SR. Therefore, this paper presents a method to decrease the error of sensed AT, taking SR into consideration. In this work, we analyzed all of the collected data of AT and SR in May 2014 and found the numerical correspondence between AT error (ATE and SR. This corresponding relation was used to calculate real-time ATE according to real-time SR and to correct the error of AT in other months.

  8. An Aerosol Extinction-to-Backscatter Ratio Database Derived from the NASA Micro-Pulse Lidar Network: Applications for Space-based Lidar Observations

    Science.gov (United States)

    Welton, Ellsworth J.; Campbell, James R.; Spinhime, James D.; Berkoff, Timothy A.; Holben, Brent; Tsay, Si-Chee; Bucholtz, Anthony

    2004-01-01

    Backscatter lidar signals are a function of both backscatter and extinction. Hence, these lidar observations alone cannot separate the two quantities. The aerosol extinction-to-backscatter ratio, S, is the key parameter required to accurately retrieve extinction and optical depth from backscatter lidar observations of aerosol layers. S is commonly defined as 4*pi divided by the product of the single scatter albedo and the phase function at 180-degree scattering angle. Values of S for different aerosol types are not well known, and are even more difficult to determine when aerosols become mixed. Here we present a new lidar-sunphotometer S database derived from Observations of the NASA Micro-Pulse Lidar Network (MPLNET). MPLNET is a growing worldwide network of eye-safe backscatter lidars co-located with sunphotometers in the NASA Aerosol Robotic Network (AERONET). Values of S for different aerosol species and geographic regions will be presented. A framework for constructing an S look-up table will be shown. Look-up tables of S are needed to calculate aerosol extinction and optical depth from space-based lidar observations in the absence of co-located AOD data. Applications for using the new S look-up table to reprocess aerosol products from NASA's Geoscience Laser Altimeter System (GLAS) will be discussed.

  9. Artificial Neural Networks to reconstruct incomplete satellite data: application to the Mediterranean Sea Surface Temperature

    Directory of Open Access Journals (Sweden)

    E. Pisoni

    2008-02-01

    Full Text Available Satellite data can be very useful in applications where extensive spatial information is needed, but sometimes missing data due to presence of clouds can affect data quality. In this study a methodology for pre-processing sea surface temperature (SST data is proposed. The methodology, that processes measures in the visible wavelength, is based on an Artificial Neural Network (ANN system. The effectiveness of the procedure has been also evaluated comparing results obtained using an interpolation method. After the methodology has been identified, a validation is performed on 3 different episodes representative of SST variability in the Mediterranean sea. The proposed technique can process SST NOAA/AVHRR data to simulate severe storm episodes by means of prognostic meteorological models.

  10. Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

    KAUST Repository

    Ryu, Duchwan

    2013-03-01

    The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  11. The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

    International Nuclear Information System (INIS)

    Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

    1992-01-01

    Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

  12. Temperature- and supply voltage-independent time references for wireless sensor networks

    CERN Document Server

    De Smedt, Valentijn; Dehaene, Wim

    2015-01-01

    This book investigates the possible circuit solutions to overcome the temperature- and supply voltage-sensitivity of fully-integrated time references for ultra-low-power communication in wireless sensor networks. The authors provide an elaborate theoretical introduction and literature study to enable full understanding of the design challenges and shortcomings of current oscillator implementations.  Furthermore, a closer look to the short-term as well as the long-term frequency stability of integrated oscillators is taken. Next, a design strategy is developed and applied to 5 different oscillator topologies and 1 sensor interface.All 6 implementations are subject to an elaborate study of frequency stability, phase noise, and power consumption. In the final chapter all blocks are compared to the state of the art. The main goals of this book are: • to provide a comprehensive overview of timing issues and solutions in wireless sensor networks; • to gain understanding of all underlying mechanisms by starti...

  13. Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Roberto Carlos dos; Pereira, Iraci Martinez, E-mail: rcsantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

  14. Development of neural network driven fuzzy controller for outlet sodium temperature of DHX

    International Nuclear Information System (INIS)

    Okusa, Kyoichi; Endou, Akira; Yoshikawa, Shinji; Ozawa, Kenji

    1996-01-01

    Fuzzy controls are capable to exquisitely control non-linear dynamic systems in wide operating range, using linguistic description to define the control law. However the selection and the definition of the fuzzy rules and sets require a tedious trial and error process based on experience. As a method to overcome this limitation, a neural network driven fuzzy control (NDF), where the learning capability of the neural network (NN) is used to build the fuzzy rules and sets, is presented in this paper. In the NDF control the IF part of a fuzzy control is represented by a multilayer NN while the THEN part is represented by a series of multilayer NNs which calculate the desirable control action. In this work the usual stepwise variable reduction method, used for the selection of the input variable in the THEN part NN, is replaced with a learning algorithm with forgetting mechanism that realizes the automatic reduction of the variables and the tuning up of all the fuzzy control law i.e. the membership function. The NDF has been successfully applied to control the outlet sodium temperature of a dump heat exchanger (DHX) of a FBR plant

  15. Time response prediction of Brazilian Nuclear Power Plant temperature sensors using neural networks

    International Nuclear Information System (INIS)

    Santos, Roberto Carlos dos; Pereira, Iraci Martinez

    2011-01-01

    This work presents the results of the time constants values predicted from ANN using Angra I Brazilian nuclear power plant data. The signals obtained from LCSR loop current step response test sensors installed in the process presents noise end fluctuations that are inherent of operational conditions. Angra I nuclear power plant has 20 RTDs as part of the protection reactor system. The results were compared with those obtained from traditional way. Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. An in-situ test method called LCSR - loop current step response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using neural networks. With the use of neural networks it will not be necessary to use the LCSR transformation to determine sensor's time constant and this leads to more robust results. (author)

  16. Prediction of hydrate formation temperature by both statistical models and artificial neural network approaches

    International Nuclear Information System (INIS)

    Zahedi, Gholamreza; Karami, Zohre; Yaghoobi, Hamed

    2009-01-01

    In this study, various estimation methods have been reviewed for hydrate formation temperature (HFT) and two procedures have been presented. In the first method, two general correlations have been proposed for HFT. One of the correlations has 11 parameters, and the second one has 18 parameters. In order to obtain constants in proposed equations, 203 experimental data points have been collected from literatures. The Engineering Equation Solver (EES) and Statistical Package for the Social Sciences (SPSS) soft wares have been employed for statistical analysis of the data. Accuracy of the obtained correlations also has been declared by comparison with experimental data and some recent common used correlations. In the second method, HFT is estimated by artificial neural network (ANN) approach. In this case, various architectures have been checked using 70% of experimental data for training of ANN. Among the various architectures multi layer perceptron (MLP) network with trainlm training algorithm was found as the best architecture. Comparing the obtained ANN model results with 30% of unseen data confirms ANN excellent estimation performance. It was found that ANN is more accurate than traditional methods and even our two proposed correlations for HFT estimation.

  17. Application of Entropy Ensemble Filter in Neural Network Forecasts of Tropical Pacific Sea Surface Temperatures

    Directory of Open Access Journals (Sweden)

    Hossein Foroozand

    2018-03-01

    Full Text Available Recently, the Entropy Ensemble Filter (EEF method was proposed to mitigate the computational cost of the Bootstrap AGGregatING (bagging method. This method uses the most informative training data sets in the model ensemble rather than all ensemble members created by the conventional bagging. In this study, we evaluate, for the first time, the application of the EEF method in Neural Network (NN modeling of El Nino-southern oscillation. Specifically, we forecast the first five principal components (PCs of sea surface temperature monthly anomaly fields over tropical Pacific, at different lead times (from 3 to 15 months, with a three-month increment for the period 1979–2017. We apply the EEF method in a multiple-linear regression (MLR model and two NN models, one using Bayesian regularization and one Levenberg-Marquardt algorithm for training, and evaluate their performance and computational efficiency relative to the same models with conventional bagging. All models perform equally well at the lead time of 3 and 6 months, while at higher lead times, the MLR model’s skill deteriorates faster than the nonlinear models. The neural network models with both bagging methods produce equally successful forecasts with the same computational efficiency. It remains to be shown whether this finding is sensitive to the dataset size.

  18. TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

    Science.gov (United States)

    Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

    2017-05-05

    Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.

  19. Overcoming the sign problem at finite temperature: Quantum tensor network for the orbital eg model on an infinite square lattice

    Science.gov (United States)

    Czarnik, Piotr; Dziarmaga, Jacek; Oleś, Andrzej M.

    2017-07-01

    The variational tensor network renormalization approach to two-dimensional (2D) quantum systems at finite temperature is applied to a model suffering the notorious quantum Monte Carlo sign problem—the orbital eg model with spatially highly anisotropic orbital interactions. Coarse graining of the tensor network along the inverse temperature β yields a numerically tractable 2D tensor network representing the Gibbs state. Its bond dimension D —limiting the amount of entanglement—is a natural refinement parameter. Increasing D we obtain a converged order parameter and its linear susceptibility close to the critical point. They confirm the existence of finite order parameter below the critical temperature Tc, provide a numerically exact estimate of Tc, and give the critical exponents within 1 % of the 2D Ising universality class.

  20. Hot metal temperature prediction by neural networks in the blast furnace; Prediccion mediante redes neuronales de la temperatura de arrabio de un horno alto. Temperatura subyacente de arrabio

    Energy Technology Data Exchange (ETDEWEB)

    Cantera, C.; Jimenez, J.; Varela, I.; Formoso, A.

    2002-07-01

    Based on a simplified model, the underlying temperature criteria is proposed as a method to study the temperature trends in a blast furnace. As an application, a neural network able to forecast hot metal temperatures from 2 to 16 h in advance (with decreasing precision) has been built. This neural network has been designed to work at real time in a production plant. (Author)

  1. Numerical databases in marine biology

    Digital Repository Service at National Institute of Oceanography (India)

    Sarupria, J.S.; Bhargava, R.M.S.

    stream_size 9 stream_content_type text/plain stream_name Natl_Workshop_Database_Networking_Mar_Biol_1991_45.pdf.txt stream_source_info Natl_Workshop_Database_Networking_Mar_Biol_1991_45.pdf.txt Content-Encoding ISO-8859-1 Content-Type... text/plain; charset=ISO-8859-1 ...

  2. NORPERM, the Norwegian Permafrost Database - a TSP NORWAY IPY legacy

    Science.gov (United States)

    Juliussen, H.; Christiansen, H. H.; Strand, G. S.; Iversen, S.; Midttømme, K.; Rønning, J. S.

    2010-10-01

    NORPERM, the Norwegian Permafrost Database, was developed at the Geological Survey of Norway during the International Polar Year (IPY) 2007-2009 as the main data legacy of the IPY research project Permafrost Observatory Project: A Contribution to the Thermal State of Permafrost in Norway and Svalbard (TSP NORWAY). Its structural and technical design is described in this paper along with the ground temperature data infrastructure in Norway and Svalbard, focussing on the TSP NORWAY permafrost observatory installations in the North Scandinavian Permafrost Observatory and Nordenskiöld Land Permafrost Observatory, being the primary data providers of NORPERM. Further developments of the database, possibly towards a regional database for the Nordic area, are also discussed. The purpose of NORPERM is to store ground temperature data safely and in a standard format for use in future research. The IPY data policy of open, free, full and timely release of IPY data is followed, and the borehole metadata description follows the Global Terrestrial Network for Permafrost (GTN-P) standard. NORPERM is purely a temperature database, and the data is stored in a relation database management system and made publically available online through a map-based graphical user interface. The datasets include temperature time series from various depths in boreholes and from the air, snow cover, ground-surface or upper ground layer recorded by miniature temperature data-loggers, and temperature profiles with depth in boreholes obtained by occasional manual logging. All the temperature data from the TSP NORWAY research project is included in the database, totalling 32 temperature time series from boreholes, 98 time series of micrometeorological temperature conditions, and 6 temperature depth profiles obtained by manual logging in boreholes. The database content will gradually increase as data from previous and future projects are added. Links to near real-time permafrost temperatures, obtained

  3. Prospects of real-time ion temperature and rotation profiles based on neural-network charge exchange analysis

    Energy Technology Data Exchange (ETDEWEB)

    Koenig, R W.T.; Von Hellermann, M [Commission of the European Communities, Abingdon (United Kingdom). JET Joint Undertaking; Svensson, J [Royal Inst. of Tech., Stockholm (Sweden)

    1994-07-01

    A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V{sub rot}). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs.

  4. Prospects of real-time ion temperature and rotation profiles based on neural-network charge exchange analysis

    International Nuclear Information System (INIS)

    Koenig, R.W.T.; Von Hellermann, M.

    1994-01-01

    A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V rot ). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs

  5. A Neural Network Based Intelligent Predictive Sensor for Cloudiness, Solar Radiation and Air Temperature

    Science.gov (United States)

    Ferreira, Pedro M.; Gomes, João M.; Martins, Igor A. C.; Ruano, António E.

    2012-01-01

    Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature. PMID:23202230

  6. The Prediction of Surface Tension of Ternary Mixtures at Different Temperatures Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ali Khazaei

    2014-07-01

    Full Text Available In this work, artificial neural network (ANN has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocarbon components. The ANN model has been developed as a function of temperature, critical properties, and acentric factor of the mixture according to conventional corresponding-state models. 80% of the data points were employed for training ANN and the remaining data were utilized for testing the generated model. The average absolute relative deviations (AARD% of the model for the training set, the testing set, and the total data points were obtained 1.69, 1.86, and 1.72 respectively. Comparing the results with Flory theory, Brok-Bird equation, and group contribution theory has proved the high prediction capability of the attained model.

  7. Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF neural networks

    Directory of Open Access Journals (Sweden)

    Tatar Afshin

    2016-03-01

    Full Text Available Raw natural gases usually contain water. It is very important to remove the water from these gases through dehydration processes due to economic reasons and safety considerations. One of the most important methods for water removal from these gases is using dehydration units which use Triethylene glycol (TEG. The TEG concentration at which all water is removed and dew point characteristics of mixture are two important parameters, which should be taken into account in TEG dehydration system. Hence, developing a reliable and accurate model to predict the performance of such a system seems to be very important in gas engineering operations. This study highlights the use of intelligent modeling techniques such as Multilayer perceptron (MLP and Radial Basis Function Neural Network (RBF-ANN to predict the equilibrium water dew point in a stream of natural gas based on the TEG concentration of stream and contractor temperature. Literature data set used in this study covers temperatures from 10 °C to 80 °C and TEG concentrations from 90.000% to 99.999%. Results showed that both models are accurate in prediction of experimental data and the MLP model gives more accurate predictions compared to RBF model.

  8. Automated classification of seismic sources in a large database: a comparison of Random Forests and Deep Neural Networks.

    Science.gov (United States)

    Hibert, Clement; Stumpf, André; Provost, Floriane; Malet, Jean-Philippe

    2017-04-01

    In the past decades, the increasing quality of seismic sensors and capability to transfer remotely large quantity of data led to a fast densification of local, regional and global seismic networks for near real-time monitoring of crustal and surface processes. This technological advance permits the use of seismology to document geological and natural/anthropogenic processes (volcanoes, ice-calving, landslides, snow and rock avalanches, geothermal fields), but also led to an ever-growing quantity of seismic data. This wealth of seismic data makes the construction of complete seismicity catalogs, which include earthquakes but also other sources of seismic waves, more challenging and very time-consuming as this critical pre-processing stage is classically done by human operators and because hundreds of thousands of seismic signals have to be processed. To overcome this issue, the development of automatic methods for the processing of continuous seismic data appears to be a necessity. The classification algorithm should satisfy the need of a method that is robust, precise and versatile enough to be deployed to monitor the seismicity in very different contexts. In this study, we evaluate the ability of machine learning algorithms for the analysis of seismic sources at the Piton de la Fournaise volcano being Random Forest and Deep Neural Network classifiers. We gather a catalog of more than 20,000 events, belonging to 8 classes of seismic sources. We define 60 attributes, based on the waveform, the frequency content and the polarization of the seismic waves, to parameterize the seismic signals recorded. We show that both algorithms provide similar positive classification rates, with values exceeding 90% of the events. When trained with a sufficient number of events, the rate of positive identification can reach 99%. These very high rates of positive identification open the perspective of an operational implementation of these algorithms for near-real time monitoring of

  9. Relational databases

    CERN Document Server

    Bell, D A

    1986-01-01

    Relational Databases explores the major advances in relational databases and provides a balanced analysis of the state of the art in relational databases. Topics covered include capture and analysis of data placement requirements; distributed relational database systems; data dependency manipulation in database schemata; and relational database support for computer graphics and computer aided design. This book is divided into three sections and begins with an overview of the theory and practice of distributed systems, using the example of INGRES from Relational Technology as illustration. The

  10. A normalization method for combination of laboratory test results from different electronic healthcare databases in a distributed research network.

    Science.gov (United States)

    Yoon, Dukyong; Schuemie, Martijn J; Kim, Ju Han; Kim, Dong Ki; Park, Man Young; Ahn, Eun Kyoung; Jung, Eun-Young; Park, Dong Kyun; Cho, Soo Yeon; Shin, Dahye; Hwang, Yeonsoo; Park, Rae Woong

    2016-03-01

    Distributed research networks (DRNs) afford statistical power by integrating observational data from multiple partners for retrospective studies. However, laboratory test results across care sites are derived using different assays from varying patient populations, making it difficult to simply combine data for analysis. Additionally, existing normalization methods are not suitable for retrospective studies. We normalized laboratory results from different data sources by adjusting for heterogeneous clinico-epidemiologic characteristics of the data and called this the subgroup-adjusted normalization (SAN) method. Subgroup-adjusted normalization renders the means and standard deviations of distributions identical under population structure-adjusted conditions. To evaluate its performance, we compared SAN with existing methods for simulated and real datasets consisting of blood urea nitrogen, serum creatinine, hematocrit, hemoglobin, serum potassium, and total bilirubin. Various clinico-epidemiologic characteristics can be applied together in SAN. For simplicity of comparison, age and gender were used to adjust population heterogeneity in this study. In simulations, SAN had the lowest standardized difference in means (SDM) and Kolmogorov-Smirnov values for all tests (p normalization performed better than normalization using other methods. The SAN method is applicable in a DRN environment and should facilitate analysis of data integrated across DRN partners for retrospective observational studies. Copyright © 2015 John Wiley & Sons, Ltd.

  11. ORACLE DATABASE SECURITY

    OpenAIRE

    Cristina-Maria Titrade

    2011-01-01

    This paper presents some security issues, namely security database system level, data level security, user-level security, user management, resource management and password management. Security is a constant concern in the design and database development. Usually, there are no concerns about the existence of security, but rather how large it should be. A typically DBMS has several levels of security, in addition to those offered by the operating system or network. Typically, a DBMS has user a...

  12. Biofuel Database

    Science.gov (United States)

    Biofuel Database (Web, free access)   This database brings together structural, biological, and thermodynamic data for enzymes that are either in current use or are being considered for use in the production of biofuels.

  13. Community Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This excel spreadsheet is the result of merging at the port level of several of the in-house fisheries databases in combination with other demographic databases such...

  14. Wood Modification at High Temperature and Pressurized Steam: a Relational Model of Mechanical Properties Based on a Neural Network

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2015-07-01

    Full Text Available Thermally modified wood has high dimensional stability and biological durability.But if the process parameters of thermal modification are not appropriate, then there will be a decline in the physical properties of wood.A neural network algorithm was employed in this study to establish the relationship between the process parameters of high-temperature and high-pressure thermal modification and the mechanical properties of the wood. Three important parameters: temperature, relative humidity, and treatment time, were considered as the inputs to the neural network. Back propagation (BP neural network and radial basis function (RBF neural network models for prediction were built and compared. The comparison showed that the RBF neural network model had advantages in network structure, convergence speed, and generalization capacity. On this basis, the inverse model, reflecting the relationship between the process parameters and the mechanical properties of wood, was established. Given the desired mechanical properties of the wood, the thermal modification process parameters could be inversely optimized and predicted. The results indicated that the model has good learning ability and generalization capacity. This is of great importance for the theoretical and applicational studies of the thermal modification of wood.

  15. Temperature-induced phase transition in hydrogels of interpenetrating networks poly(N-isopropylmethacrylamide)/poly(N-isopropylacrylamide)

    Czech Academy of Sciences Publication Activity Database

    Šťastná, J.; Hanyková, L.; Sedláková, Zdeňka; Valentová, H.; Spěváček, Jiří

    2013-01-01

    Roč. 291, č. 10 (2013), s. 2409-2417 ISSN 0303-402X R&D Projects: GA ČR GA202/09/1281 Institutional support: RVO:61389013 Keywords : temperature-induced volume phase transition * poly (N-isopropylmethacrylamide) poly (Nisopropylacrylamide) interpenetrating network * 1H NMR spectroscopy Subject RIV: CD - Macromolecular Chemistry Impact factor: 2.410, year: 2013

  16. Silver nanowires network encapsulated by low temperature sol-gel ZnO for transparent flexible electrodes with ambient stability

    Science.gov (United States)

    Shin, Wonjung; Cho, Wonki; Baik, Seung Jae

    2018-01-01

    As a geometrically engineered realization of transparent electrode, Ag nanowires network is promising for its superior characteristics both on electrical conductivity and optical transmittance. However, for a potential commercialization of Ag nanowires network, further investigations on encapsulation materials are necessary to prevent degradation caused by ambient aging. In addition, the temperature range of the coating process for the encapsulation material needs to be low enough to prevent degradation of polymer substrates during the film coating processes, when considering emerging flexible device application of transparent electrodes. We present experimental results showing that low temperature sol-gel ZnO processed under 130 °C is an effective encapsulation material preventing ambient oxidation of Ag nanowires network without degrading electrical, optical, and mechanical properties.

  17. Database Administrator

    Science.gov (United States)

    Moore, Pam

    2010-01-01

    The Internet and electronic commerce (e-commerce) generate lots of data. Data must be stored, organized, and managed. Database administrators, or DBAs, work with database software to find ways to do this. They identify user needs, set up computer databases, and test systems. They ensure that systems perform as they should and add people to the…

  18. Using an artificial neural network to predict carbon dioxide compressibility factor at high pressure and temperature

    Energy Technology Data Exchange (ETDEWEB)

    Mohagheghian, Erfan [Memorial University of Newfoundland, St. John' s (Canada); Zafarian-Rigaki, Habiballah; Motamedi-Ghahfarrokhi, Yaser; Hemmati-Sarapardeh, Abdolhossein [Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

    2015-10-15

    Carbon dioxide injection, which is widely used as an enhanced oil recovery (EOR) method, has the potential of being coupled with CO{sub 2} sequestration and reducing the emission of greenhouse gas. Hence, knowing the compressibility factor of carbon dioxide is of a vital significance. Compressibility factor (Z-factor) is traditionally measured through time consuming, expensive and cumbersome experiments. Hence, developing a fast, robust and accurate model for its estimation is necessary. In this study, a new reliable model on the basis of feed forward artificial neural networks is presented to predict CO{sub 2} compressibility factor. Reduced temperature and pressure were selected as the input parameters of the proposed model. To evaluate and compare the results of the developed model with pre-existing models, both statistical and graphical error analyses were employed. The results indicated that the proposed model is more reliable and accurate compared to pre-existing models in a wide range of temperature (up to 1,273.15 K) and pressure (up to 140MPa). Furthermore, by employing the relevancy factor, the effect of pressure and temprature on the Z-factor of CO{sub 2} was compared for below and above the critical pressure of CO{sub 2}, and the physcially expected trends were observed. Finally, to identify the probable outliers and applicability domain of the proposed ANN model, both numerical and graphical techniques based on Leverage approach were performed. The results illustrated that only 1.75% of the experimental data points were located out of the applicability domain of the proposed model. As a result, the developed model is reliable for the prediction of CO{sub 2} compressibility factor.

  19. Hydrogen bond network relaxation in aqueous polyelectrolyte solutions: the effect of temperature

    International Nuclear Information System (INIS)

    Sarti, S; Bordi, F; Truzzolillo, D

    2012-01-01

    Dielectric spectroscopy data over the range 100 MHz-40 GHz allow for a reliable analysis of two of the major relaxation phenomena for polyelectrolytes (PE) in water. Within this range, the dielectric relaxation of pure water is dominated by a near-Debye process at ν = 18.5 GHz corresponding to a relaxation time of τ = 8.4 ps at 25 °C. This mode is commonly attributed to the cooperative relaxation specific to liquids forming a hydrogen bond network (HBN) and arising from long range H-bond-mediated dipole-dipole interactions. The presence of charged polymers in water partially modifies the dielectric characteristics of the orientational water molecule relaxation due to a change of the dielectric constant of water surrounding the charges on the polyion chain. We report experimental results on the effect of the presence of a standard flexible polyelectrolyte (sodium polyacrylate) on the HBN relaxation in water for different temperatures, showing that the HBN relaxation time does not change by increasing the polyelectrolyte density in water, even if relatively high concentrations are reached (0.02 monomol l -1 ≤ C ≤ 0.4 monomol l -1 ). We also find that the effect of PE addition on the HBN relaxation is not even a broadening of its distribution, rather a decrease of the spectral weight that goes beyond the pure volume fraction effect. This extra decrease is larger at low T and less evident at high T, supporting the idea that the correlation length of the water is less affected by the presence of charged flexible chains at high temperatures. (paper)

  20. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques

    Science.gov (United States)

    Kisi, Ozgur; Sanikhani, Hadi; Cobaner, Murat

    2017-08-01

    The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models' accuracy was also investigated. Including periodicity component in models' inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.

  1. Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks

    Directory of Open Access Journals (Sweden)

    Zhihong Liao

    2017-11-01

    Full Text Available A radial basis function network (RBFN method is proposed to reconstruct daily Sea surface temperatures (SSTs with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the Reynolds optimum interpolation (OI v2 daily 0.25° SST (OISST products according to the distribution of AVHRR L2p SST and in-situ SST data. Furthermore, an improved nearest neighbor cluster (INNC algorithm is designed to search for the optimal hidden knots for RBFNs from both the SST samples and the background fields. Then, the reconstructed SSTs from the RBFN method are compared with the results from the OI method. The statistical results show that the RBFN method has a better performance of reconstructing SST than the OI method in the study, and that the average RMSE is 0.48 °C for the RBFN method, which is quite smaller than the value of 0.69 °C for the OI method. Additionally, the RBFN methods with different basis functions and clustering algorithms are tested, and we discover that the INNC algorithm with multi-quadric function is quite suitable for the RBFN method to reconstruct SSTs when the SST samples are sparsely distributed.

  2. The study of diffusion in network-forming liquids under pressure and temperature

    Energy Technology Data Exchange (ETDEWEB)

    Hung, P.K. [Department of Computational Physics, Hanoi University of Technology, 1Dai Co Viet, Hanoi (Viet Nam); Kien, P.H., E-mail: phkien80@gmail.com [Department of Physics, Thainguyen University of Education, 20 Luong Ngoc Quyen, Thainguyen (Viet Nam); San, L.T.; Hong, N.V. [Department of Computational Physics, Hanoi University of Technology, 1Dai Co Viet, Hanoi (Viet Nam)

    2016-11-15

    In this paper, the molecular dynamics simulation is applied to investigate the diffusion in silica liquids under different temperature and pressure. We show that the diffusion is controlled by the rate of effective SiO{sub x}→SiO{sub x±1} and OSi{sub y}→OSi{sub y±1} reaction. With increasing the pressure, the rate of reaction increases and the Si–O bond is weaker. Moreover, the reactions are not uniformly distributed in the space, but instead they happen frequently or rarely in separate regions. We also reveal two motion types: free and correlation motion. The correlation motion concerns the moving of a group of atoms which is similar to that of the diffusion of a super-molecule in the liquid. A detailed analysis of the movement of atoms from specified set shows the clustering of them which indicates structure and dynamics heterogeneity. Further, we find that the correlation motion is very important for the diffusion in network-forming liquid. The observed phenomena such as diffusion anomaly, dynamics heterogeneity and dynamical slowdown are originated from the correlation motion of atom.

  3. Prediction of Daily Global Solar Radiation by Daily Temperatures and Artificial Neural Networks in Different Climates

    Directory of Open Access Journals (Sweden)

    S. I Saedi

    2018-03-01

    Full Text Available Introduction Global solar radiation is the sum of direct, diffuse, and reflected solar radiation. Weather forecasts, agricultural practices, and solar equipment development are three major fields that need proper information about solar radiation. Furthermore, sun in regarded as a huge source of renewable and clean energy which can be used in numerous applications to get rid of environmental impacts of non-renewable fossil fuels. Therefore, easy and fast estimation of daily global solar radiation would play an effective role is these affairs. Materials and Methods This study aimed at predicting the daily global solar radiation by means of artificial neural network (ANN method, based on easy-to-gain weather data i.e. daily mean, minimum and maximum temperatures. Having a variety of climates with long-term valid weather data, Washington State, located at the northwestern part of USA was chosen for this purpose. It has a total number of 19 weather stations to cover all the State climates. First, a station with the largest number of valid historical weather data (Lind was chosen to develop, validate, and test different ANN models. Three training algorithms i.e. Levenberg – Marquardt (LM, Scaled Conjugate Gradient (SCG, and Bayesian regularization (BR were tested in one and two hidden layer networks each with up to 20 neurons to derive six best architectures. R, RMSE, MAPE, and scatter plots were considered to evaluate each network in all steps. In order to investigate the generalizability of the best six models, they were tested in other Washington State weather stations. The most accurate and general models was evaluated in an Iran sample weather station which was chosen to be Mashhad. Results and Discussion The variation of MSE for the three training functions in one hidden layer models for Lind station indicated that SCG converged weights and biases in shorter time than LM, and LM did that faster than BR. It means that SCG provided the fastest

  4. 經由校園網路存取圖書館光碟資料庫之研究 Studies on Multiuser Access Library CD-ROM Database via Campus Network

    Directory of Open Access Journals (Sweden)

    Ruey-shun Chen

    1992-06-01

    Full Text Available 無Library CD-ROM with its enormous storage, retrieval capabilities and reasonable price. It has been gradually replacing some of its printed counterpart. But one of the greatest limitation on the use of stand-alone CD-ROM workstation is that only one user can access the CD-ROM database at a time. This paper is proposed a new method to solve this problem. The method use personal computer via standard network system Ethernet high speed fiber network FADDY and standard protocol TCP/IP can access library CD-ROM database and perform a practical CD-ROM campus network system. Its advantage reduce redundant CD-ROM purchase fee and reduce damage by handed in and out and allows multiuser to access the same CD-ROM disc simultaneously.

  5. The International Haemovigilance Network Database for the Surveillance of Adverse Reactions and Events in Donors and Recipients of Blood Components: technical issues and results.

    Science.gov (United States)

    Politis, C; Wiersum, J C; Richardson, C; Robillard, P; Jorgensen, J; Renaudier, P; Faber, J-C; Wood, E M

    2016-11-01

    The International Haemovigilance Network's ISTARE is an online database for surveillance of all adverse reactions (ARs) and adverse events (AEs) associated with donation of blood and transfusion of blood components, irrespective of severity or the harm caused. ISTARE aims to unify the collection and sharing of information with a view to harmonizing best practices for haemovigilance systems around the world. Adverse reactionss and adverse events are recorded by blood component, type of reaction, severity and imputability to transfusion, using internationally agreed standard definitions. From 2006 to 2012, 125 national sets of annual aggregated data were received from 25 countries, covering 132.8 million blood components issued. The incidence of all ARs was 77.5 per 100 000 components issued, of which 25% were severe (19.1 per 100 000). Of 349 deaths (0.26 per 100 000), 58% were due to the three ARs related to the respiratory system: transfusion-associated circulatory overload (TACO, 27%), transfusion-associated acute lung injury (TRALI, 19%) and transfusion-associated dyspnoea (TAD, 12%). Cumulatively, 594 477 donor complications were reported (rate 660 per 100 000), of which 2.9% were severe. ISTARE is a well-established surveillance tool offering important contributions to international efforts to maximize transfusion safety. © 2016 International Society of Blood Transfusion.

  6. Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database.

    Science.gov (United States)

    Chen-Ying Hung; Wei-Chen Chen; Po-Tsun Lai; Ching-Heng Lin; Chi-Chun Lee

    2017-07-01

    Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.

  7. DSSTOX STRUCTURE-SEARCHABLE PUBLIC TOXICITY DATABASE NETWORK: CURRENT PROGRESS AND NEW INITIATIVES TO IMPROVE CHEMO-BIOINFORMATICS CAPABILITIES

    Science.gov (United States)

    The EPA DSSTox website (http://www/epa.gov/nheerl/dsstox) publishes standardized, structure-annotated toxicity databases, covering a broad range of toxicity disciplines. Each DSSTox database features documentation written in collaboration with the source authors and toxicity expe...

  8. Identification of Gene Modules Associated with Low Temperatures Response in Bambara Groundnut by Network-Based Analysis.

    Directory of Open Access Journals (Sweden)

    Venkata Suresh Bonthala

    Full Text Available Bambara groundnut (Vigna subterranea (L. Verdc. is an African legume and is a promising underutilized crop with good seed nutritional values. Low temperature stress in a number of African countries at night, such as Botswana, can effect the growth and development of bambara groundnut, leading to losses in potential crop yield. Therefore, in this study we developed a computational pipeline to identify and analyze the genes and gene modules associated with low temperature stress responses in bambara groundnut using the cross-species microarray technique (as bambara groundnut has no microarray chip coupled with network-based analysis. Analyses of the bambara groundnut transcriptome using cross-species gene expression data resulted in the identification of 375 and 659 differentially expressed genes (p<0.01 under the sub-optimal (23°C and very sub-optimal (18°C temperatures, respectively, of which 110 genes are commonly shared between the two stress conditions. The construction of a Highest Reciprocal Rank-based gene co-expression network, followed by its partition using a Heuristic Cluster Chiseling Algorithm resulted in 6 and 7 gene modules in sub-optimal and very sub-optimal temperature stresses being identified, respectively. Modules of sub-optimal temperature stress are principally enriched with carbohydrate and lipid metabolic processes, while most of the modules of very sub-optimal temperature stress are significantly enriched with responses to stimuli and various metabolic processes. Several transcription factors (from MYB, NAC, WRKY, WHIRLY & GATA classes that may regulate the downstream genes involved in response to stimulus in order for the plant to withstand very sub-optimal temperature stress were highlighted. The identified gene modules could be useful in breeding for low-temperature stress tolerant bambara groundnut varieties.

  9. MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

    Science.gov (United States)

    Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

    2014-05-01

    spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.

  10. Federal databases

    International Nuclear Information System (INIS)

    Welch, M.J.; Welles, B.W.

    1988-01-01

    Accident statistics on all modes of transportation are available as risk assessment analytical tools through several federal agencies. This paper reports on the examination of the accident databases by personal contact with the federal staff responsible for administration of the database programs. This activity, sponsored by the Department of Energy through Sandia National Laboratories, is an overview of the national accident data on highway, rail, air, and marine shipping. For each mode, the definition or reporting requirements of an accident are determined and the method of entering the accident data into the database is established. Availability of the database to others, ease of access, costs, and who to contact were prime questions to each of the database program managers. Additionally, how the agency uses the accident data was of major interest

  11. National Transportation Atlas Databases : 2013.

    Science.gov (United States)

    2013-01-01

    The National Transportation Atlas Databases 2013 (NTAD2013) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  12. National Transportation Atlas Databases : 2015.

    Science.gov (United States)

    2015-01-01

    The National Transportation Atlas Databases 2015 (NTAD2015) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  13. National Transportation Atlas Databases : 2014.

    Science.gov (United States)

    2014-01-01

    The National Transportation Atlas Databases 2014 (NTAD2014) is a set of nationwide geographic datasets of transportation facilities, transportation networks, associated infrastructure, and other political and administrative entities. These datasets i...

  14. Silicon microgyroscope temperature prediction and control system based on BP neural network and Fuzzy-PID control method

    International Nuclear Information System (INIS)

    Xia, Dunzhu; Kong, Lun; Hu, Yiwei; Ni, Peizhen

    2015-01-01

    We present a novel silicon microgyroscope (SMG) temperature prediction and control system in a narrow space. As the temperature of SMG is closely related to its drive mode frequency and driving voltage, a temperature prediction model can be established based on the BP neural network. The simulation results demonstrate that the established temperature prediction model can estimate the temperature in the range of −40 to 60 °C with an error of less than ±0.05 °C. Then, a temperature control system based on the combination of fuzzy logic controller and the increment PID control method is proposed. The simulation results prove that the Fuzzy-PID controller has a smaller steady state error, less rise time and better robustness than the PID controller. This is validated by experimental results that show the Fuzzy-PID control method can achieve high precision in keeping the SMG temperature stable at 55 °C with an error of less than 0.2 °C. The scale factor can be stabilized at 8.7 mV/°/s with a temperature coefficient of 33 ppm °C −1 . ZRO (zero rate output) instability is decreased from 1.10°/s (9.5 mV) to 0.08°/s (0.7 mV) when the temperature control system is implemented over an ambient temperature range of −40 to 60 °C. (paper)

  15. Database Replication

    CERN Document Server

    Kemme, Bettina

    2010-01-01

    Database replication is widely used for fault-tolerance, scalability and performance. The failure of one database replica does not stop the system from working as available replicas can take over the tasks of the failed replica. Scalability can be achieved by distributing the load across all replicas, and adding new replicas should the load increase. Finally, database replication can provide fast local access, even if clients are geographically distributed clients, if data copies are located close to clients. Despite its advantages, replication is not a straightforward technique to apply, and

  16. Refactoring databases evolutionary database design

    CERN Document Server

    Ambler, Scott W

    2006-01-01

    Refactoring has proven its value in a wide range of development projects–helping software professionals improve system designs, maintainability, extensibility, and performance. Now, for the first time, leading agile methodologist Scott Ambler and renowned consultant Pramodkumar Sadalage introduce powerful refactoring techniques specifically designed for database systems. Ambler and Sadalage demonstrate how small changes to table structures, data, stored procedures, and triggers can significantly enhance virtually any database design–without changing semantics. You’ll learn how to evolve database schemas in step with source code–and become far more effective in projects relying on iterative, agile methodologies. This comprehensive guide and reference helps you overcome the practical obstacles to refactoring real-world databases by covering every fundamental concept underlying database refactoring. Using start-to-finish examples, the authors walk you through refactoring simple standalone databas...

  17. Modeling of High Temperature Oxidation Behavior of FeCrAl Alloy by using Artificial Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Joon; Ryu, Ho Jin [KAIST, Daejeon (Korea, Republic of)

    2016-10-15

    Refractory alloys are candidate materials for replacing current zirconium-base cladding of light water reactors and they retain significant creep resistance and mechanical strength at high temperatures up to 1500 ℃ due to their high melting temperature. Thermal neutron cross sections of refractory metals are higher than that of zirconium, however the loss of neutron can be overcome by reducing cladding thickness which can be facilitated with enhanced mechanical properties. However, most refractory metals show the poor oxidation resistance at a high temperature. Oxidation behaviors of the various compositions of FeCrAl alloys in high temperature conditions were modeled by using Bayesian neural network. The automatic relevance determination (ARD) technique represented the influence of the composition of alloying elements on the oxidation resistance of FeCrAl alloys. This model can be utilized to understand the tendency of oxidation behavior along the composition of each element and prove the applicability of neural network modeling for the development of new cladding material of light water reactors.

  18. Neurostimulation options for failed back surgery syndrome: The need for rational and objective measurements. Proposal of an international clinical network using an integrated database and health economic analysis: the PROBACK network.

    Science.gov (United States)

    Rigoard, P; Slavin, K

    2015-03-01

    In the context of failed back surgery syndrome (FBSS) treatment, the current practice in neurostimulation varies from center-to-center and most clinical decisions are based on an individual diagnosis. Neurostimulation evaluation tools and pain relief assessment are of major concern, as they now constitute one of the main biases of clinical trials. Moreover, the proliferation of technological devices, in a fertile and unsatisfied market, fosters and only furthers the confusion. There are three options available to apply scientific debates to our daily neurostimulation practice: intentional ignorance, standardized evidence-based practice or alternative data mining approach. In view of the impossibility of conducting multiple randomized clinical trials comparing various devices, one by one, the proposed concept would be to redefine the indications and the respective roles of the various spinal cord and peripheral nerve stimulation devices with large-scale computational modeling/data mining approach, by conducting a multicenter prospective database registry, supported by a clinician's global network called "PROBACK". We chose to specifically analyze 6 parameters: device coverage performance/coverage selectivity/persistence of the long-term electrical response (technical criteria) and comparative mapping of patient pain relief/persistence of the long-term clinical response/safety and complications occurrence (clinical criteria). Two types of analysis will be performed: immediate analysis (including cost analysis) and computational analysis, i.e. demonstration of the robustness of certain correlations of variables, in order to extract response predictors. By creating an international prospective database, the purpose of the PROBACK project was to set up a process of extraction and comparative analysis of data derived from the selection, implantation and follow-up of FBSS patients candidates for implanted neurostimulation. This evaluation strategy should help to change

  19. Regional variations of basal cell carcinoma incidence in the U.K. using The Health Improvement Network database (2004-10).

    Science.gov (United States)

    Musah, A; Gibson, J E; Leonardi-Bee, J; Cave, M R; Ander, E L; Bath-Hextall, F

    2013-11-01

    Basal cell carcinoma (BCC) is one of the most common types of nonmelanoma skin cancer affecting the white population; however, little is known about how the incidence varies across the U.K. To determine the variation in BCC throughout the U.K. Data from 2004 to 2010 were obtained from The Health Improvement Network database. European and world age-standardized incidence rates (EASRs and WASRs, respectively) were obtained for country-level estimates and levels of socioeconomic deprivation, while strategic health-authority-level estimates were directly age and sex standardized to the U.K. standard population. Incidence-rate ratios were estimated using multivariable Poisson regression models. The overall EASR and WASR of BCC in the U.K. were 98.6 per 100,000 person-years and 66.9 per 100,000 person-years, respectively. Regional-level incidence rates indicated a significant geographical variation in the distribution of BCC, which was more pronounced in the southern parts of the country. The South East Coast had the highest BCC rate followed by South Central, Wales and the South West. Incidence rates were substantially higher in the least deprived groups and we observed a trend of decreasing incidence with increasing levels of deprivation (P < 0.001). Finally, in terms of age groups, the largest annual increase was observed among those aged 30-49 years. Basal cell carcinoma is an increasing health problem in the U.K.; the southern regions of the U.K. and those in the least deprived groups had a higher incidence of BCC. Our findings indicate an increased incidence of BCC for younger age groups below 49 years. © 2013 British Association of Dermatologists.

  20. Impact of Socioeconomic Status on Patients Supported With a Left Ventricular Assist Device: An Analysis of the UNOS Database (United Network for Organ Sharing).

    Science.gov (United States)

    Clerkin, Kevin J; Garan, Arthur Reshad; Wayda, Brian; Givens, Raymond C; Yuzefpolskaya, Melana; Nakagawa, Shunichi; Takeda, Koji; Takayama, Hiroo; Naka, Yoshifumi; Mancini, Donna M; Colombo, Paolo C; Topkara, Veli K

    2016-10-01

    Low socioeconomic status (SES) is a known risk factor for heart failure, mortality among those with heart failure, and poor post heart transplant (HT) outcomes. This study sought to determine whether SES is associated with decreased waitlist survival while on left ventricular assist device (LVADs) support and after HT. A total of 3361 adult patients bridged to primary HT with an LVAD between May 2004 and April 2014 were identified in the UNOS database (United Network for Organ Sharing). SES was measured using the Agency for Healthcare Research and Quality SES index using data from the 2014 American Community Survey. In the study cohort, SES did not have an association with the combined end point of death or delisting on LVAD support (P=0.30). In a cause-specific unadjusted model, those in the top (hazard ratio, 1.55; 95% confidence interval, 1.14-2.11; P=0.005) and second greatest SES quartile (hazard ratio 1.50; 95% confidence interval, 1.10-2.04; P=0.01) had an increased risk of death on device support compared with the lowest SES quartile. Adjusting for clinical risk factors mitigated the increased risk. There was no association between SES and complications. Post-HT survival, both crude and adjusted, was decreased for patients in the lowest quartile of SES index compared with all other SES quartiles. Freedom from waitlist death or delisting was not affected by SES. Patients with a higher SES had an increased unadjusted risk of waitlist mortality during LVAD support, which was mitigated by adjusting for increased comorbid conditions. Low SES was associated with worse post-HT outcomes. Further study is needed to confirm and understand a differential effect of SES on post-transplant outcomes that was not seen during LVAD support before HT. © 2016 American Heart Association, Inc.

  1. Incidence, treatment and recurrence of endometriosis in a UK-based population analysis using data from The Health Improvement Network and the Hospital Episode Statistics database.

    Science.gov (United States)

    Cea Soriano, Lucia; López-Garcia, Esther; Schulze-Rath, Renate; Garcia Rodríguez, Luis A

    2017-10-01

    This retrospective study used medical records from The Health Improvement Network (THIN) and Hospital Episode Statistics (HES) database to evaluate endometriosis (incidence, treatment and need for recurrent invasive procedures) in the general UK population. Women aged 12-54 years between January 2000 and December 2010, with a Read code for endometriosis, were identified in THIN. Cases were validated by manual review of free-text comments in medical records and responses to physician questionnaires. False-negative cases were identified among women with Read codes for hysterectomy or dysmenorrhea. Prescriptions of medical therapies for endometriosis were identified in THIN. Cases of single and recurrent invasive procedures were identified in women with medical records in both THIN and HES. Overall, 5087 women had a Read code for endometriosis, corresponding to an incidence of 1.02 (95% confidence interval [CI]: 0.99-1.05) per 1000 person-years. After case validation, the estimate was 1.46 (95% CI: 1.43-1.50) per 1000 person-years. Medical therapy was prescribed to 55.5% of women with endometriosis in the first year after diagnosis. In total, 48.3% of women received invasive treatment during the study period; approximately one-fifth of these women required further invasive treatment, mainly in the 3 years after the index procedure. Using Read codes as the only method to identify women with endometriosis underestimates incidence. Over half of women with recorded endometriosis are prescribed medical therapy in the first year after diagnosis. Women with diagnosed endometriosis are at risk of requiring recurrent invasive procedures.

  2. RDD Databases

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This database was established to oversee documents issued in support of fishery research activities including experimental fishing permits (EFP), letters of...

  3. Snowstorm Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Snowstorm Database is a collection of over 500 snowstorms dating back to 1900 and updated operationally. Only storms having large areas of heavy snowfall (10-20...

  4. Dealer Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dealer reporting databases contain the primary data reported by federally permitted seafood dealers in the northeast. Electronic reporting was implemented May 1,...

  5. A system design for distributed energy generation in low temperature district heating (LTDH) networks

    OpenAIRE

    Jones, Sean; Gillott, Mark C.; Boukhanouf, Rabah; Walker, Gavin S.; Tunzi, Michele; Tetlow, David; Rodrigues, Lucélia Taranto; Sumner, M.

    2017-01-01

    Project SCENIC (Smart Controlled Energy Networks Integrated in Communities) involves connecting properties at the University of Nottingham’s Creative Energy Homes test site in a community scale, integrated heat and power network. Controls will be developed to allow for the most effective heat load allocation and power distribution scenarios. Furthermore, the system will develop the prosumer concept, where consumers are both buyers and sellers of energy in both heat and power systems. \\ud \\ud ...

  6. National database

    DEFF Research Database (Denmark)

    Kristensen, Helen Grundtvig; Stjernø, Henrik

    1995-01-01

    Artikel om national database for sygeplejeforskning oprettet på Dansk Institut for Sundheds- og Sygeplejeforskning. Det er målet med databasen at samle viden om forsknings- og udviklingsaktiviteter inden for sygeplejen.......Artikel om national database for sygeplejeforskning oprettet på Dansk Institut for Sundheds- og Sygeplejeforskning. Det er målet med databasen at samle viden om forsknings- og udviklingsaktiviteter inden for sygeplejen....

  7. The magnet database system

    International Nuclear Information System (INIS)

    Baggett, P.; Delagi, N.; Leedy, R.; Marshall, W.; Robinson, S.L.; Tompkins, J.C.

    1991-01-01

    This paper describes the current status of MagCom, a central database of SSC magnet information that is available to all magnet scientists via network connections. The database has been designed to contain the specifications and measured values of important properties for major materials, plus configuration information (specifying which individual items were used in each cable, coil, and magnet) and the test results on completed magnets. These data will help magnet scientists to track and control the production process and to correlate the performance of magnets with the properties of their constituents

  8. Numerical Simulations of Evaporating Sprays in High Pressure and Temperature Operating Conditions (Engine Combustion Network [ECN])

    Science.gov (United States)

    2014-05-01

    temperature effect in nonreacting and reacting diesel sprays using a novel injector , and imaging diagnostics for liquid phase penetration, light-off...ambient conditions. A single hole, modern common rail injector with an injector diameter of 90 µ (Bosch CRIN 2.4) is used at typical diesel injection...Temperature (K) 363 Ambient temperature (K) 900 Nozzle Diameter (mm) 0.09 Ambient density (kg/m3) 22.8 Injection Duration (ms) 1.5 Number of injector holes

  9. A spatial model for a stream networks of Citarik River with the environmental variables: potential of hydrogen (PH) and temperature

    Science.gov (United States)

    Bachrudin, A.; Mohamed, N. B.; Supian, S.; Sukono; Hidayat, Y.

    2018-03-01

    Application of existing geostatistical theory of stream networks provides a number of interesting and challenging problems. Most of statistical tools in the traditional geostatistics have been based on a Euclidean distance such as autocovariance functions, but for stream data is not permissible since it deals with a stream distance. To overcome this autocovariance developed a model based on the distance the flow with using convolution kernel approach (moving average construction). Spatial model for a stream networks is widely used to monitor environmental on a river networks. In a case study of a river in province of West Java, the objective of this paper is to analyze a capability of a predictive on two environmental variables, potential of hydrogen (PH) and temperature using ordinary kriging. Several the empirical results show: (1) The best fit of autocovariance functions for temperature and potential hydrogen (ph) of Citarik River is linear which also yields the smallest root mean squared prediction error (RMSPE), (2) the spatial correlation values between the locations on upstream and on downstream of Citarik river exhibit decreasingly

  10. A method of optimized neural network by L-M algorithm to transformer winding hot spot temperature forecasting

    Science.gov (United States)

    Wei, B. G.; Wu, X. Y.; Yao, Z. F.; Huang, H.

    2017-11-01

    Transformers are essential devices of the power system. The accurate computation of the highest temperature (HST) of a transformer’s windings is very significant, as for the HST is a fundamental parameter in controlling the load operation mode and influencing the life time of the insulation. Based on the analysis of the heat transfer processes and the thermal characteristics inside transformers, there is taken into consideration the influence of factors like the sunshine, external wind speed etc. on the oil-immersed transformers. Experimental data and the neural network are used for modeling and protesting of the HST, and furthermore, investigations are conducted on the optimization of the structure and algorithms of neutral network are conducted. Comparison is made between the measured values and calculated values by using the recommended algorithm of IEC60076 and by using the neural network algorithm proposed by the authors; comparison that shows that the value computed with the neural network algorithm approximates better the measured value than the value computed with the algorithm proposed by IEC60076.

  11. Experiment Databases

    Science.gov (United States)

    Vanschoren, Joaquin; Blockeel, Hendrik

    Next to running machine learning algorithms based on inductive queries, much can be learned by immediately querying the combined results of many prior studies. Indeed, all around the globe, thousands of machine learning experiments are being executed on a daily basis, generating a constant stream of empirical information on machine learning techniques. While the information contained in these experiments might have many uses beyond their original intent, results are typically described very concisely in papers and discarded afterwards. If we properly store and organize these results in central databases, they can be immediately reused for further analysis, thus boosting future research. In this chapter, we propose the use of experiment databases: databases designed to collect all the necessary details of these experiments, and to intelligently organize them in online repositories to enable fast and thorough analysis of a myriad of collected results. They constitute an additional, queriable source of empirical meta-data based on principled descriptions of algorithm executions, without reimplementing the algorithms in an inductive database. As such, they engender a very dynamic, collaborative approach to experimentation, in which experiments can be freely shared, linked together, and immediately reused by researchers all over the world. They can be set up for personal use, to share results within a lab or to create open, community-wide repositories. Here, we provide a high-level overview of their design, and use an existing experiment database to answer various interesting research questions about machine learning algorithms and to verify a number of recent studies.

  12. A Generic Data Harmonization Process for Cross-linked Research and Network Interaction. Construction and Application for the Lung Cancer Phenotype Database of the German Center for Lung Research.

    Science.gov (United States)

    Firnkorn, D; Ganzinger, M; Muley, T; Thomas, M; Knaup, P

    2015-01-01

    Joint data analysis is a key requirement in medical research networks. Data are available in heterogeneous formats at each network partner and their harmonization is often rather complex. The objective of our paper is to provide a generic approach for the harmonization process in research networks. We applied the process when harmonizing data from three sites for the Lung Cancer Phenotype Database within the German Center for Lung Research. We developed a spreadsheet-based solution as tool to support the harmonization process for lung cancer data and a data integration procedure based on Talend Open Studio. The harmonization process consists of eight steps describing a systematic approach for defining and reviewing source data elements and standardizing common data elements. The steps for defining common data elements and harmonizing them with local data definitions are repeated until consensus is reached. Application of this process for building the phenotype database led to a common basic data set on lung cancer with 285 structured parameters. The Lung Cancer Phenotype Database was realized as an i2b2 research data warehouse. Data harmonization is a challenging task requiring informatics skills as well as domain knowledge. Our approach facilitates data harmonization by providing guidance through a uniform process that can be applied in a wide range of projects.

  13. Improvement of the European thermodynamic database NUCLEA

    Energy Technology Data Exchange (ETDEWEB)

    Brissoneau, L.; Journeau, C.; Piluso, P. [CEA Cadarache, DEN, F-13108 St Paul Les Durance (France); Bakardjieva, S. [Acad Sci Czech Republic, Inst Inorgan Chem, CZ-25068 Rez (Czech Republic); Barrachin, M. [Inst Radioprotect and Surete Nucl, St Paul Les Durance (France); Bechta, S. [NITI, Aleksandrov Res Inst Technol, Sosnovyi Bor (Russian Federation); Bottomley, D. [Commiss European Communities, Joint Res Ctr, Inst Transuranium Elements, D-76125 Karlsruhe (Germany); Cheynet, B.; Fischer, E. [Thermodata, F-38400 St Martin Dheres (France); Kiselova, M. [Nucl Res Inst UJV, Rez 25068 (Czech Republic); Mezentseva, L. [Russian Acad Sci, Inst Silicate Chem, St Petersburg (Russian Federation)

    2010-07-01

    Modelling of corium behaviour during a severe accident requires knowledge of the phases present at equilibrium for a given corium composition, temperature and pressure. The thermodynamic database NUCLEA in combination with a Gibbs Energy minimizer is the European reference tool to achieve this goal. This database has been improved thanks to the analysis of bibliographical data and to EU-funded experiments performed within the SARNET network, PLINIUS as well as the ISTC CORPHAD and EVAN projects. To assess the uncertainty range associated with Energy Dispersive X-ray analyses, a round-robin exercise has been launched in which a UO{sub 2}-containing corium-concrete interaction sample from VULCANO has been analyzed by three European laboratories with satisfactorily small differences. (authors)

  14. DMPD: The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling inflammation. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available ncellular signaling networks controlling inflammation. Ringwood L, Li L. Cytokine. 2008 Apr;42(1):1-7. Epub ...ases (IRAKs) incellular signaling networks controlling inflammation. PubmedID 182...49132 Title The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling

  15. THE TEMPERATURE EFFECT IN SECONDARY COSMIC RAYS (MUONS) OBSERVED AT THE GROUND: ANALYSIS OF THE GLOBAL MUON DETECTOR NETWORK DATA

    Energy Technology Data Exchange (ETDEWEB)

    De Mendonça, R. R. S.; Braga, C. R.; Echer, E.; Dal Lago, A.; Rockenbach, M.; Schuch, N. J. [Space Geophysics Division, National Institute for Space Research, São José dos Campos, SP, 12227-010 (Brazil); Munakata, K.; Kato, C. [Physics Department, Shinshu University, Matsumoto, Nagano, 390-8621 (Japan); Kuwabara, T. [Graduate School of Science, Chiba University, Chiba City, Chiba 263-8522 (Japan); Kozai, M. [Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (ISAS/JAXA), Sagamihara, Kanagawa 252-5210 (Japan); Al Jassar, H. K.; Sharma, M. M. [Physics Department, Kuwait University, Kuwait City, 13060 (Kuwait); Tokumaru, M. [Solar Terrestrial Environment Laboratory, Nagoya University, Nagoya, Aichi, 464-8601 (Japan); Duldig, M. L.; Humble, J. E. [School of Physical Sciences, University of Tasmania, Hobart, Tasmania, 7001 (Australia); Evenson, P. [Bartol Research Institute, Department of Physics and Astronomy, University of Delaware, Newark, DE 19716 (United States); Sabbah, I. [Department of Natural Sciences, College of Health Sciences, Public Authority for Applied Education and Training, Kuwait City, 72853 (Kuwait)

    2016-10-20

    The analysis of cosmic ray intensity variation seen by muon detectors at Earth's surface can help us to understand astrophysical, solar, interplanetary and geomagnetic phenomena. However, before comparing cosmic ray intensity variations with extraterrestrial phenomena, it is necessary to take into account atmospheric effects such as the temperature effect. In this work, we analyzed this effect on the Global Muon Detector Network (GMDN), which is composed of four ground-based detectors, two in the northern hemisphere and two in the southern hemisphere. In general, we found a higher temperature influence on detectors located in the northern hemisphere. Besides that, we noticed that the seasonal temperature variation observed at the ground and at the altitude of maximum muon production are in antiphase for all GMDN locations (low-latitude regions). In this way, contrary to what is expected in high-latitude regions, the ground muon intensity decrease occurring during summertime would be related to both parts of the temperature effect (the negative and the positive). We analyzed several methods to describe the temperature effect on cosmic ray intensity. We found that the mass weighted method is the one that best reproduces the seasonal cosmic ray variation observed by the GMDN detectors and allows the highest correlation with long-term variation of the cosmic ray intensity seen by neutron monitors.

  16. THE TEMPERATURE EFFECT IN SECONDARY COSMIC RAYS (MUONS) OBSERVED AT THE GROUND: ANALYSIS OF THE GLOBAL MUON DETECTOR NETWORK DATA

    International Nuclear Information System (INIS)

    De Mendonça, R. R. S.; Braga, C. R.; Echer, E.; Dal Lago, A.; Rockenbach, M.; Schuch, N. J.; Munakata, K.; Kato, C.; Kuwabara, T.; Kozai, M.; Al Jassar, H. K.; Sharma, M. M.; Tokumaru, M.; Duldig, M. L.; Humble, J. E.; Evenson, P.; Sabbah, I.

    2016-01-01

    The analysis of cosmic ray intensity variation seen by muon detectors at Earth's surface can help us to understand astrophysical, solar, interplanetary and geomagnetic phenomena. However, before comparing cosmic ray intensity variations with extraterrestrial phenomena, it is necessary to take into account atmospheric effects such as the temperature effect. In this work, we analyzed this effect on the Global Muon Detector Network (GMDN), which is composed of four ground-based detectors, two in the northern hemisphere and two in the southern hemisphere. In general, we found a higher temperature influence on detectors located in the northern hemisphere. Besides that, we noticed that the seasonal temperature variation observed at the ground and at the altitude of maximum muon production are in antiphase for all GMDN locations (low-latitude regions). In this way, contrary to what is expected in high-latitude regions, the ground muon intensity decrease occurring during summertime would be related to both parts of the temperature effect (the negative and the positive). We analyzed several methods to describe the temperature effect on cosmic ray intensity. We found that the mass weighted method is the one that best reproduces the seasonal cosmic ray variation observed by the GMDN detectors and allows the highest correlation with long-term variation of the cosmic ray intensity seen by neutron monitors.

  17. Temperature Effect in Secondary Cosmic Rays (MUONS) Observed at the Ground: Analysis of the Global MUON Detector Network Data

    Science.gov (United States)

    de Mendonça, R. R. S.; Braga, C. R.; Echer, E.; Dal Lago, A.; Munakata, K.; Kuwabara, T.; Kozai, M.; Kato, C.; Rockenbach, M.; Schuch, N. J.; Jassar, H. K. Al; Sharma, M. M.; Tokumaru, M.; Duldig, M. L.; Humble, J. E.; Evenson, P.; Sabbah, I.

    2016-10-01

    The analysis of cosmic ray intensity variation seen by muon detectors at Earth's surface can help us to understand astrophysical, solar, interplanetary and geomagnetic phenomena. However, before comparing cosmic ray intensity variations with extraterrestrial phenomena, it is necessary to take into account atmospheric effects such as the temperature effect. In this work, we analyzed this effect on the Global Muon Detector Network (GMDN), which is composed of four ground-based detectors, two in the northern hemisphere and two in the southern hemisphere. In general, we found a higher temperature influence on detectors located in the northern hemisphere. Besides that, we noticed that the seasonal temperature variation observed at the ground and at the altitude of maximum muon production are in antiphase for all GMDN locations (low-latitude regions). In this way, contrary to what is expected in high-latitude regions, the ground muon intensity decrease occurring during summertime would be related to both parts of the temperature effect (the negative and the positive). We analyzed several methods to describe the temperature effect on cosmic ray intensity. We found that the mass weighted method is the one that best reproduces the seasonal cosmic ray variation observed by the GMDN detectors and allows the highest correlation with long-term variation of the cosmic ray intensity seen by neutron monitors.

  18. Database Perspectives on Blockchains

    OpenAIRE

    Cohen, Sara; Zohar, Aviv

    2018-01-01

    Modern blockchain systems are a fresh look at the paradigm of distributed computing, applied under assumptions of large-scale public networks. They can be used to store and share information without a trusted central party. There has been much effort to develop blockchain systems for a myriad of uses, ranging from cryptocurrencies to identity control, supply chain management, etc. None of this work has directly studied the fundamental database issues that arise when using blockchains as the u...

  19. Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

    KAUST Repository

    Ryu, Duchwan; Liang, Faming; Mallick, Bani K.

    2013-01-01

    be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle

  20. Artificial neural network model to predict slag viscosity over a broad range of temperatures and slag compositions

    Energy Technology Data Exchange (ETDEWEB)

    Duchesne, Marc A. [Chemical and Biological Engineering Department, University of Ottawa, 161 Louis Pasteur, Ottawa, Ont. (Canada); CanmetENERGY, 1 Haanel Drive, Ottawa, Ontario (Canada); Macchi, Arturo [Chemical and Biological Engineering Department, University of Ottawa, 161 Louis Pasteur, Ottawa, Ont. (Canada); Lu, Dennis Y.; Hughes, Robin W.; McCalden, David; Anthony, Edward J. [CanmetENERGY, 1 Haanel Drive, Ottawa, Ontario (Canada)

    2010-08-15

    Threshold slag viscosity heuristics are often used for the initial assessment of coal gasification projects. Slag viscosity predictions are also required for advanced combustion and gasification models. Due to unsatisfactory performance of theoretical equations, an artificial neural network model was developed to predict slag viscosity over a broad range of temperatures and slag compositions. This model outperforms other slag viscosity models, resulting in an average error factor of 5.05 which is lower than the best obtained with other available models. Genesee coal ash viscosity predictions were made to investigate the effect of adding Canadian limestone and dolomite. The results indicate that magnesium in the fluxing agent provides a greater viscosity reduction than calcium for the threshold slag tapping temperature range. (author)

  1. Maintaining the Database for Information Object Analysis, Intent, Dissemination and Enhancement (IOAIDE) and the US Army Research Laboratory Campus Sensor Network (ARL CSN)

    Science.gov (United States)

    2017-01-01

    operations as well as basic knowledge of Microsoft Structured Query Language Server Management Studio (2014 or 2016). 15. SUBJECT TERMS Microsoft SQL ...designed and is maintained with Microsoft SQL Server Management Studio. The basic requirements for the IOAIDE/ARL CSN database development and... SQL server (2014 or 2016) installed. All images in this report were generated using Windows 10. The IOAIDE/ARL CSN database could reside on the

  2. Utilization of local area network technology and decentralized structure for nuclear reactor core temperature monitoring

    International Nuclear Information System (INIS)

    Casella, M.; Peirano, F.

    1986-01-01

    The present system concerns Superphenix type reactors. It is a new version of system for monitoring the reactor core temperatures. It has been designed to minimize the cost and the wiring complexity because of the large number of channels (800). For this, equipments are arranged on the roof slab of the reactor with a single link to the control room; from which the name Integrated Treatment of Core Temperatures: TITC 1500 and the natural choice of a distributed system. This system monitors permanently the thermal state of the core a Superphenix type reactor. This monitoring system aims at detecting anomalies of core temperature rise, releasing automatic shutdown (safety), and providing to the monitoring systems not concerned safety the information concerning the core [fr

  3. Rheology, Morphology and Temperature Dependency of Nanotube Networks in Polycarbonate/Multiwalled Carbon Nanotube Composites

    International Nuclear Information System (INIS)

    Abbasi, Samaneh; Carreau, Pierre J.; Derdouri, Abdessalem

    2008-01-01

    We present several issues related to the state of dispersion and rheological behavior of polycarbonate/multiwalled carbon nanotube (MWCNT) composites. The composites were prepared by diluting a commercial masterbatch containing 15 wt% nanotubes using optimized melt-mixing conditions. The state of dispersion was then analyzed by scanning and transmission electron microscopy (SEM, TEM). Rheological characterization was also used to assess the final morphology. Further, it was found that the rheological percolation threshold decreased significantly with increasing temperature and finally reached a constant value. This is described in terms of the Brownian motion, which increases with temperature. However, by increasing the nanotube content, the temperature effects on the complex viscosity at low frequency decreased significantly. Finally, the percolation thresholds were found to be approximately equal to 0.3 and 2 wt% for rheological and electrical conductivity measurements, respectively

  4. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  5. Spatial Statistical Network Models for Stream and River Temperatures in the Chesapeake Bay Watershed

    Science.gov (United States)

    Numerous metrics have been proposed to describe stream/river thermal regimes, and researchers are still struggling with the need to describe thermal regimes in a parsimonious fashion. Regional temperature models are needed for characterizing and mapping current stream thermal re...

  6. DMPD: Translational mini-review series on Toll-like receptors: networks regulated byToll-like receptors mediate innate and adaptive immunity. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17223959 Translational mini-review series on Toll-like receptors: networks regulate...ol. 2007 Feb;147(2):199-207. (.png) (.svg) (.html) (.csml) Show Translational mini-review series on Toll-lik... immunity. PubmedID 17223959 Title Translational mini-review series on Toll-like receptors: networks regulat

  7. First diagnosis and management of incontinence in older people with and without dementia in primary care: a cohort study using The Health Improvement Network primary care database.

    Directory of Open Access Journals (Sweden)

    Robert L Grant

    2013-08-01

    Full Text Available Dementia is one of the most disabling and burdensome diseases. Incontinence in people with dementia is distressing, adds to carer burden, and influences decisions to relocate people to care homes. Successful and safe management of incontinence in people with dementia presents additional challenges. The aim of this study was to investigate the rates of first diagnosis in primary care of urinary and faecal incontinence among people aged 60-89 with dementia, and the use of medication or indwelling catheters for urinary incontinence.We extracted data on 54,816 people aged 60-89 with dementia and an age-gender stratified sample of 205,795 people without dementia from 2001 to 2010 from The Health Improvement Network (THIN, a United Kingdom primary care database. THIN includes data on patients and primary care consultations but does not identify care home residents. Rate ratios were adjusted for age, sex, and co-morbidity using multilevel Poisson regression. The rates of first diagnosis per 1,000 person-years at risk (95% confidence interval for urinary incontinence in the dementia cohort, among men and women, respectively, were 42.3 (40.9-43.8 and 33.5 (32.6-34.5. In the non-dementia cohort, the rates were 19.8 (19.4-20.3 and 18.6 (18.2-18.9. The rates of first diagnosis for faecal incontinence in the dementia cohort were 11.1 (10.4-11.9 and 10.1 (9.6-10.6. In the non-dementia cohort, the rates were 3.1 (2.9-3.3 and 3.6 (3.5-3.8. The adjusted rate ratio for first diagnosis of urinary incontinence was 3.2 (2.7-3.7 in men and 2.7 (2.3-3.2 in women, and for faecal incontinence was 6.0 (5.1-7.0 in men and 4.5 (3.8-5.2 in women. The adjusted rate ratio for pharmacological treatment of urinary incontinence was 2.2 (1.4-3.7 for both genders, and for indwelling urinary catheters was 1.6 (1.3-1.9 in men and 2.3 (1.9-2.8 in women.Compared with those without a dementia diagnosis, those with a dementia diagnosis have approximately three times the rate of

  8. Low temperature hall effect investigation of conducting polymer-carbon nanotubes composite network.

    Science.gov (United States)

    Bahrami, Afarin; Talib, Zainal Abidin; Yunus, Wan Mahmood Mat; Behzad, Kasra; M Abdi, Mahnaz; Din, Fasih Ud

    2012-11-14

    Polypyrrole (PPy) and polypyrrole-carboxylic functionalized multi wall carbon nanotube composites (PPy/f-MWCNT) were synthesized by in situ chemical oxidative polymerization of pyrrole on the carbon nanotubes (CNTs). The structure of the resulting complex nanotubes was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The effects of f-MWCNT concentration on the electrical properties of the resulting composites were studied at temperatures between 100 K and 300 K. The Hall mobility and Hall coefficient of PPy and PPy/f-MWCNT composite samples with different concentrations of f-MWCNT were measured using the van der Pauw technique. The mobility decreased slightly with increasing temperature, while the conductivity was dominated by the gradually increasing carrier density.

  9. Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module

    Directory of Open Access Journals (Sweden)

    Yuan-Chieh Lo

    2018-02-01

    Full Text Available Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe. Its specification, through experimental test, achieves to the precision ±(0.1 + 0.0029|t| °C, resolution 0.00489 °C, power consumption 7 mW, and size Ø40 mm × 27 mm. For the software, the heat transfer characteristics of the machine tool spindle correlative to rotating speed are derived based on the theory of heat transfer and empirical formula. The predictive TNM of spindles was developed by grey-box estimation and experimental results. Even under such complicated operating conditions as various speeds and different initial conditions, the experiments validate that the present modeling methodology provides a robust and reliable tool for the temperature prediction with normalized mean square error of 99.5% agreement, and the present approach is transferable to the other spindles with a similar structure. For realizing the edge computing in smart manufacturing, a reduced-order TNM is constructed by Model Order Reduction (MOR technique and implemented into the real-time embedded system.

  10. Chip-to-chip SnO2 nanowire network sensors for room temperature H2 detection

    Science.gov (United States)

    Köck, A.; Brunet, E.; Mutinati, G. C.; Maier, T.; Steinhauer, S.

    2012-06-01

    The employment of nanowires is a very powerful strategy to improve gas sensor performance. We demonstrate a gas sensor device, which is based on silicon chip-to-chip synthesis of ultralong tin oxide (SnO2) nanowires. The sensor device employs an interconnected SnO2 nanowire network configuration, which exhibits a huge surface-to-volume ratio and provides full access of the target gas to the nanowires. The chip-to-chip SnO2 nanowire device is able to detect a H2 concentration of only 20 ppm in synthetic air with ~ 60% relative humidity at room temperature. At an operating temperature of 300°C a concentration of 50 ppm H2 results in a sensitivity of 5%. At this elevated temperature the sensor shows a linear response in a concentration range between 10 ppm and 100 ppm H2. The SnO2-nanowire fabrication procedure based on spray pyrolysis and subsequent annealing is performed at atmospheric pressure, requires no vacuum and allows upscale of the substrate to a wafer size. 3D-integration with CMOS chips is proposed as viable way for practical realization of smart nanowire based gas sensor devices for the consumer market.

  11. Comparison of instrumental and interpolated meteorological data-based summer temperature reconstructions on Mt. Taibai in the Qinling Mountains, northwestern China

    Science.gov (United States)

    Qin, Jin; Bai, Hongying; Su, Kai; Liu, Rongjuan; Zhai, Danping; Wang, Jun; Li, Shuheng; Zhou, Qi; Li, Bin

    2018-01-01

    Previous dendroclimatical studies have been based on the relationship between tree growth and instrumental climate data recorded at lower land meteorological stations, but the climate conditions somehow differ between sampling sites and distant population centers. Thus, in this study, we performed a comparison between the 152-year reconstruction of June to July mean air temperature on the basis of interpolated meteorological data and instrumental meteorological data. The reconstruction explained 38.7% of the variance in the interpolated temperature data (37.2% after the degrees of freedom were adjusted) and 39.6% of the variance in the instrumental temperature data (38.4% after adjustment for loss of degrees of freedom) during the period 1962-2013 AD. The first global warming (the 1920s) and recent warming (1990-2013) found from the reconstructed temperature series match reasonably well with two other reported summer temperature reconstructions from north-central China. Cold periods occurred three times during 1866-1885, 1901-1921, and 1981-2000, while hot periods occurred four times during 1886-1900, 1922-1933, 1953-1966, and 2001-2007. The extreme warm (cold) years are coherent with the documentary drought (flood) events. Significant 31-22-year, 22-18-year, and 12-8-year cycles indicate major fluctuations in regional temperatures may reflect large-scale climatic shifts.

  12. Database of Information technology resources

    OpenAIRE

    Barzda, Erlandas

    2005-01-01

    The subject of this master work is the internet information resource database. This work also handles the problems of old information systems which do not meet the new contemporary requirements. The aim is to create internet information system, based on object-oriented technologies and tailored to computer users’ needs. The internet information database system helps computers administrators to get the all needed information about computers network elements and easy to register all changes int...

  13. Knitting Relational Documentary Networks: The Database Meta-Documentary Filming Revolution as a paradigm of bringing interactive audio-visual archives alive

    NARCIS (Netherlands)

    Wiehl, Anna

    2016-01-01

    abstractOne phenomenon in the emerging field of digital documentary are experiments with rhizomatic interfaces and database-logics to bring audio-visual archives 'alive'. A paradigm hereof is Filming Revolution (2015), an interactive platform which gathers and interlinks films of the uprisings in

  14. Temperature-controlled two new Co(II) compounds with distinct topological networks: Syntheses, crystal structures and catalytic properties

    Science.gov (United States)

    Meng, Qing-Hua; Long, Xu; Liu, Jing-Li; Zhang, Shuan; Zhang, Guang-Hui

    2018-04-01

    Two new Co(II) coordination compounds, namely [Co2(bptc)(bpp)2]n (1) and [Co(bptc)0.5(bpp)]n (2) (H4bptc = biphenyl-3,3‧,5,5‧-tetracarboxylic acid, bpp = 1,3-di(4-pyridyl)propane), have been hydrothermally synthesized from the same reactants via tuning the reaction temperature. Single crystal X-ray diffraction analyses revealed that both 1 and 2 feature 2D sheet motifs. Topological analyses revealed that compounds 1 and 2 show distinct topological networks. Under the weak Van der Waals interactions, the 2D sheet motifs of compounds 1 and 2 are further packed into 2D→3D interdigitated supramolecular frameworks. Moreover, the two Co(II) compounds show high catalytic activities for degradation of methyl orange (MO) in a Fenten-like process.

  15. The magnet database system

    International Nuclear Information System (INIS)

    Ball, M.J.; Delagi, N.; Horton, B.; Ivey, J.C.; Leedy, R.; Li, X.; Marshall, B.; Robinson, S.L.; Tompkins, J.C.

    1992-01-01

    The Test Department of the Magnet Systems Division of the Superconducting Super Collider Laboratory (SSCL) is developing a central database of SSC magnet information that will be available to all magnet scientists at the SSCL or elsewhere, via network connections. The database contains information on the magnets' major components, configuration information (specifying which individual items were used in each cable, coil, and magnet), measurements made at major fabrication stages, and the test results on completed magnets. These data will facilitate the correlation of magnet performance with the properties of its constituents. Recent efforts have focused on the development of procedures for user-friendly access to the data, including displays in the format of the production open-quotes travelerclose quotes data sheets, standard summary reports, and a graphical interface for ad hoc queues and plots

  16. An Embedded Sensor Network for Measuring Elevation Effects on Temperature, Humidity, and Evapotranspiration Within a Tropical Alpine Valley

    Science.gov (United States)

    Hellstrom, R. A.; Mark, B. G.

    2006-12-01

    Conditions of glacier recession in the seasonally dry tropical Peruvian Andes motivates research to better constrain the hydrological balance in alpine valleys. Studies suggest that glaciers in the tropical Andes are particularly sensitive to seasonal humidity flux due to the migration of the Intertropical Convergence Zone. However, there is an outstanding need to better measure and model the spatiotemporal variability of energy and water budgets within pro-glacial valleys. In this context, we introduce a novel embedded network of low- cost, discrete temperature and humidity microloggers and an automatic weather station installed in the Llanganuco valley of the Cordillera Blanca. This paper presents data recorded over a full annual cycle (2004- 2005) and reports on network design and results during the dry and wet seasons. The transect of sensors ranging from about 3500 to 4700 m reveal seasonally characteristic diurnal fluctuations in up-valley lapse rate. A process-based water balance model (Brook90) examines the influence of meteorological forcing on evapotranspiration (ET) rates in the valley. The model results suggest that cloud-free daylight conditions enhances ET during the wet season. ET was insignificant throughout the dry season. In addition, we report on the effects of elevation on ET.

  17. Physical database design using Oracle

    CERN Document Server

    Burleson, Donald K

    2004-01-01

    INTRODUCTION TO ORACLE PHYSICAL DESIGNPrefaceRelational Databases and Physical DesignSystems Analysis and Physical Database DesignIntroduction to Logical Database DesignEntity/Relation ModelingBridging between Logical and Physical ModelsPhysical Design Requirements Validation PHYSICAL ENTITY DESIGN FOR ORACLEData Relationships and Physical DesignMassive De-Normalization: STAR Schema DesignDesigning Class HierarchiesMaterialized Views and De-NormalizationReferential IntegrityConclusionORACLE HARDWARE DESIGNPlanning the Server EnvironmentDesigning the Network Infrastructure for OracleOracle Netw

  18. The magnet components database system

    International Nuclear Information System (INIS)

    Baggett, M.J.; Leedy, R.; Saltmarsh, C.; Tompkins, J.C.

    1990-01-01

    The philosophy, structure, and usage MagCom, the SSC magnet components database, are described. The database has been implemented in Sybase (a powerful relational database management system) on a UNIX-based workstation at the Superconducting Super Collider Laboratory (SSCL); magnet project collaborators can access the database via network connections. The database was designed to contain the specifications and measured values of important properties for major materials, plus configuration information (specifying which individual items were used in each cable, coil, and magnet) and the test results on completed magnets. These data will facilitate the tracking and control of the production process as well as the correlation of magnet performance with the properties of its constituents. 3 refs., 10 figs

  19. The magnet components database system

    International Nuclear Information System (INIS)

    Baggett, M.J.; Leedy, R.; Saltmarsh, C.; Tompkins, J.C.

    1990-01-01

    The philosophy, structure, and usage of MagCom, the SSC magnet components database, are described. The database has been implemented in Sybase (a powerful relational database management system) on a UNIX-based workstation at the Superconducting Super Collider Laboratory (SSCL); magnet project collaborators can access the database via network connections. The database was designed to contain the specifications and measured values of important properties for major materials, plus configuration information (specifying which individual items were used in each cable, coil, and magnet) and the test results on completed magnets. The data will facilitate the tracking and control of the production process as well as the correlation of magnet performance with the properties of its constituents. 3 refs., 9 figs

  20. Stackfile Database

    Science.gov (United States)

    deVarvalho, Robert; Desai, Shailen D.; Haines, Bruce J.; Kruizinga, Gerhard L.; Gilmer, Christopher

    2013-01-01

    This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

  1. The Effects of Temperature and Salinity on Mg Incorporation in Planktonic Foraminifera Globigerinoides ruber (white): Results from a Global Sediment Trap Mg/Ca Database

    Science.gov (United States)

    Gray, W. R.; Weldeab, S.; Lea, D. W.

    2015-12-01

    Mg/Ca in Globigerinoides ruber is arguably the most important proxy for sea surface temperature (SST) in tropical and sub tropical regions, and as such guides our understanding of past climatic change in these regions. However, the sensitivity of Mg/Ca to salinity is debated; while analysis of foraminifera grown in cultures generally indicates a sensitivity of 3 - 6% per salinity unit, core-top studies have suggested a much higher sensitivity of between 15 - 27% per salinity unit, bringing the utility of Mg/Ca as a SST proxy into dispute. Sediment traps circumvent the issues of dissolution and post-depositional calcite precipitation that hamper core-top calibration studies, whilst allowing the analysis of foraminifera that have calcified under natural conditions within a well constrained period of time. We collated previously published sediment trap/plankton tow G. ruber (white) Mg/Ca data, and generated new Mg/Ca data from a sediment trap located in the highly-saline tropical North Atlantic, close to West Africa. Calcification temperature and salinity were calculated for the time interval represented by each trap/tow sample using World Ocean Atlas 2013 data. The resulting dataset comprises >240 Mg/Ca measurements (in the size fraction 150 - 350 µm), that span a temperature range of 18 - 28 °C and 33.6 - 36.7 PSU. Multiple regression of the dataset reveals a temperature sensitivity of 7 ± 0.4% per °C (p < 2.2*10-16) and a salinity sensitivity of 4 ± 1% per salinity unit (p = 2*10-5). Application of this calibration has significant implications for both the magnitude and timing of glacial-interglacial temperature changes when variations in salinity are accounted for.

  2. Computer networks for financial activity management, control and statistics of databases of economic administration at the Joint Institute for Nuclear Research

    International Nuclear Information System (INIS)

    Tyupikova, T.V.; Samoilov, V.N.

    2003-01-01

    Modern information technologies urge natural sciences to further development. But it comes together with evaluation of infrastructures, to spotlight favorable conditions for the development of science and financial base in order to prove and protect legally new research. Any scientific development entails accounting and legal protection. In the report, we consider a new direction in software, organization and control of common databases on the example of the electronic document handling, which functions in some departments of the Joint Institute for Nuclear Research

  3. SmallSat Database

    Science.gov (United States)

    Petropulos, Dolores; Bittner, David; Murawski, Robert; Golden, Bert

    2015-01-01

    The SmallSat has an unrealized potential in both the private industry and in the federal government. Currently over 70 companies, 50 universities and 17 governmental agencies are involved in SmallSat research and development. In 1994, the U.S. Army Missile and Defense mapped the moon using smallSat imagery. Since then Smart Phones have introduced this imagery to the people of the world as diverse industries watched this trend. The deployment cost of smallSats is also greatly reduced compared to traditional satellites due to the fact that multiple units can be deployed in a single mission. Imaging payloads have become more sophisticated, smaller and lighter. In addition, the growth of small technology obtained from private industries has led to the more widespread use of smallSats. This includes greater revisit rates in imagery, significantly lower costs, the ability to update technology more frequently and the ability to decrease vulnerability of enemy attacks. The popularity of smallSats show a changing mentality in this fast paced world of tomorrow. What impact has this created on the NASA communication networks now and in future years? In this project, we are developing the SmallSat Relational Database which can support a simulation of smallSats within the NASA SCaN Compatability Environment for Networks and Integrated Communications (SCENIC) Modeling and Simulation Lab. The NASA Space Communications and Networks (SCaN) Program can use this modeling to project required network support needs in the next 10 to 15 years. The SmallSat Rational Database could model smallSats just as the other SCaN databases model the more traditional larger satellites, with a few exceptions. One being that the smallSat Database is designed to be built-to-order. The SmallSat database holds various hardware configurations that can be used to model a smallSat. It will require significant effort to develop as the research material can only be populated by hand to obtain the unique data

  4. Evolution of sp2 networks with substrate temperature in amorphous carbon films: Experiment and theory

    International Nuclear Information System (INIS)

    Gago, R.; Vinnichenko, M.; Jaeger, H.U.; Maitz, M.F.; Belov, A.Yu.; Jimenez, I.; Huang, N.; Sun, H.

    2005-01-01

    The evolution of sp 2 hybrids in amorphous carbon (a-C) films deposited at different substrate temperatures was studied experimentally and theoretically. The bonding structure of a-C films prepared by filtered cathodic vacuum arc was assessed by the combination of visible Raman spectroscopy, x-ray absorption, and spectroscopic ellipsometry, while a-C structures were generated by molecular-dynamics deposition simulations with the Brenner interatomic potential to determine theoretical sp 2 site distributions. The experimental results show a transition from tetrahedral a-C (ta-C) to sp 2 -rich structures at ∼500 K. The sp 2 hybrids are mainly arranged in chains or pairs whereas graphitic structures are only promoted for sp 2 fractions above 80%. The theoretical analysis confirms the preferred pairing of isolated sp 2 sites in ta-C, the coalescence of sp 2 clusters for medium sp 2 fractions, and the pronounced formation of rings for sp 2 fractions >80%. However, the dominance of sixfold rings is not reproduced theoretically, probably related to the functional form of the interatomic potential used

  5. Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

    Science.gov (United States)

    Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

    2012-04-01

    The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

  6. A New Prediction Model for Transformer Winding Hotspot Temperature Fluctuation Based on Fuzzy Information Granulation and an Optimized Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Li Zhang

    2017-12-01

    Full Text Available Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers.

  7. Raspberry Pi in-situ network monitoring system of groundwater flow and temperature integrated with OpenGeoSys

    Science.gov (United States)

    Park, Chan-Hee; Lee, Cholwoo

    2016-04-01

    Raspberry Pi series is a low cost, smaller than credit-card sized computers that various operating systems such as linux and recently even Windows 10 are ported to run on. Thanks to massive production and rapid technology development, the price of various sensors that can be attached to Raspberry Pi has been dropping at an increasing speed. Therefore, the device can be an economic choice as a small portable computer to monitor temporal hydrogeological data in fields. In this study, we present a Raspberry Pi system that measures a flow rate, and temperature of groundwater at sites, stores them into mysql database, and produces interactive figures and tables such as google charts online or bokeh offline for further monitoring and analysis. Since all the data are to be monitored on internet, any computers or mobile devices can be good monitoring tools at convenience. The measured data are further integrated with OpenGeoSys, one of the hydrogeological models that is also ported to the Raspberry Pi series. This leads onsite hydrogeological modeling fed by temporal sensor data to meet various needs.

  8. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Science.gov (United States)

    Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Linkosalmi, Maiju; Melih Tanis, Cemal; Tuovinen, Juha-Pekka; Nadir Arslan, Ali

    2018-01-01

    In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  9. Relational nuclear databases upon the MSU INP CDFE Web-site and Nuclear Data Centres Network CDFE activities. P7[Centre for Photonuclear Experiments Data, Moscow, Russian Federation

    Energy Technology Data Exchange (ETDEWEB)

    Boboshin, I N; Varlamov, V V; Ivanov, E M; Ivanov, S V; Peskov, N N; Stepanov, M E; Chesnokov, V V [Centre for Photonuclear Experiments Data, Moscow (Russian Federation)

    2001-07-01

    This report contains only the short review of the work carried out by the CDFE concerning the IAEA Nuclear Reaction Data Centres Network activities for the period of time from the IAEA Advisory Group Meeting (15-19 May 2000, Obninsk, Russia) till May 2001 and the description of the main results obtained.

  10. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Directory of Open Access Journals (Sweden)

    M. Peltoniemi

    2018-01-01

    Full Text Available In recent years, monitoring of the status of ecosystems using low-cost web (IP or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/. Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862. Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  11. Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms, and cancer drug design using big database mining and genome-wide next-generation sequencing data.

    Science.gov (United States)

    Li, Cheng-Wei; Chen, Bor-Sen

    2016-10-01

    Recent studies have demonstrated that cell cycle plays a central role in development and carcinogenesis. Thus, the use of big databases and genome-wide high-throughput data to unravel the genetic and epigenetic mechanisms underlying cell cycle progression in stem cells and cancer cells is a matter of considerable interest. Real genetic-and-epigenetic cell cycle networks (GECNs) of embryonic stem cells (ESCs) and HeLa cancer cells were constructed by applying system modeling, system identification, and big database mining to genome-wide next-generation sequencing data. Real GECNs were then reduced to core GECNs of HeLa cells and ESCs by applying principal genome-wide network projection. In this study, we investigated potential carcinogenic and stemness mechanisms for systems cancer drug design by identifying common core and specific GECNs between HeLa cells and ESCs. Integrating drug database information with the specific GECNs of HeLa cells could lead to identification of multiple drugs for cervical cancer treatment with minimal side-effects on the genes in the common core. We found that dysregulation of miR-29C, miR-34A, miR-98, and miR-215; and methylation of ANKRD1, ARID5B, CDCA2, PIF1, STAMBPL1, TROAP, ZNF165, and HIST1H2AJ in HeLa cells could result in cell proliferation and anti-apoptosis through NFκB, TGF-β, and PI3K pathways. We also identified 3 drugs, methotrexate, quercetin, and mimosine, which repressed the activated cell cycle genes, ARID5B, STK17B, and CCL2, in HeLa cells with minimal side-effects.

  12. Extending Database Integration Technology

    National Research Council Canada - National Science Library

    Buneman, Peter

    1999-01-01

    Formal approaches to the semantics of databases and database languages can have immediate and practical consequences in extending database integration technologies to include a vastly greater range...

  13. The AMMA database

    Science.gov (United States)

    Boichard, Jean-Luc; Brissebrat, Guillaume; Cloche, Sophie; Eymard, Laurence; Fleury, Laurence; Mastrorillo, Laurence; Moulaye, Oumarou; Ramage, Karim

    2010-05-01

    The AMMA project includes aircraft, ground-based and ocean measurements, an intensive use of satellite data and diverse modelling studies. Therefore, the AMMA database aims at storing a great amount and a large variety of data, and at providing the data as rapidly and safely as possible to the AMMA research community. In order to stimulate the exchange of information and collaboration between researchers from different disciplines or using different tools, the database provides a detailed description of the products and uses standardized formats. The AMMA database contains: - AMMA field campaigns datasets; - historical data in West Africa from 1850 (operational networks and previous scientific programs); - satellite products from past and future satellites, (re-)mapped on a regular latitude/longitude grid and stored in NetCDF format (CF Convention); - model outputs from atmosphere or ocean operational (re-)analysis and forecasts, and from research simulations. The outputs are processed as the satellite products are. Before accessing the data, any user has to sign the AMMA data and publication policy. This chart only covers the use of data in the framework of scientific objectives and categorically excludes the redistribution of data to third parties and the usage for commercial applications. Some collaboration between data producers and users, and the mention of the AMMA project in any publication is also required. The AMMA database and the associated on-line tools have been fully developed and are managed by two teams in France (IPSL Database Centre, Paris and OMP, Toulouse). Users can access data of both data centres using an unique web portal. This website is composed of different modules : - Registration: forms to register, read and sign the data use chart when an user visits for the first time - Data access interface: friendly tool allowing to build a data extraction request by selecting various criteria like location, time, parameters... The request can

  14. Management system of instrument database

    International Nuclear Information System (INIS)

    Zhang Xin

    1997-01-01

    The author introduces a management system of instrument database. This system has been developed using with Foxpro on network. The system has some characters such as clear structure, easy operation, flexible and convenient query, as well as the data safety and reliability

  15. Establishing a Dynamic Database of Blue and Fin Whale Locations from Recordings at the IMS CTBTO hydro-acoustic network. The Baleakanta Project

    Science.gov (United States)

    Le Bras, R. J.; Kuzma, H.

    2013-12-01

    Falling as they do into the frequency range of continuously recording hydrophones (15-100Hz), blue and fin whale songs are a significant source of noise on the hydro-acoustic monitoring array of the International Monitoring System (IMS) of the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO). One researcher's noise, however, can be a very interesting signal in another field of study. The aim of the Baleakanta Project (www.baleakanta.org) is to flag and catalogue these songs, using the azimuth and slowness of the signal measured at multiple hydrophones to solve for the approximate location of singing whales. Applying techniques borrowed from human speaker identification, it may even be possible to recognize the songs of particular individuals. The result will be a dynamic database of whale locations and songs with known individuals noted. This database will be of great value to marine biologists studying cetaceans, as there is no existing dataset which spans the globe over many years (more than 15 years of data have been collected by the IMS). Current whale song datasets from other sources are limited to detections made on small, temporary listening devices. The IMS song catalogue will make it possible to study at least some aspects of the global migration patterns of whales, changes in their songs over time, and the habits of individuals. It is believed that about 10 blue whale 'cultures' exist with distinct vocal patterns; the IMS song catalogue will test that number. Results and a subset of the database (delayed in time to mitigate worries over whaling and harassment of the animals) will be released over the web. A traveling museum exhibit is planned which will not only educate the public about whale songs, but will also make the CTBTO and its achievements more widely known. As a testament to the public's enduring fascination with whales, initial funding for this project has been crowd-sourced through an internet campaign.

  16. A NEW NETWORK FOR HIGHER-TEMPERATURE GAS-PHASE CHEMISTRY. I. A PRELIMINARY STUDY OF ACCRETION DISKS IN ACTIVE GALACTIC NUCLEI

    International Nuclear Information System (INIS)

    Harada, Nanase; Herbst, Eric; Wakelam, Valentine

    2010-01-01

    We present a new interstellar chemical gas-phase reaction network for time-dependent kinetics that can be used for modeling high-temperature sources up to ∼800 K. This network contains an extended set of reactions based on the Ohio State University (OSU) gas-phase chemical network. The additional reactions include processes with significant activation energies, reverse reactions, proton exchange reactions, charge exchange reactions, and collisional dissociation. Rate coefficients already in the OSU network are modified for H 2 formation on grains, ion-neutral dipole reactions, and some radiative association reactions. The abundance of H 2 O is enhanced at high temperature by hydrogenation of atomic O. Much of the elemental oxygen is in the form of water at T ≥ 300 K, leading to effective carbon-rich conditions, which can efficiently produce carbon-chain species such as C 2 H 2 . At higher temperatures, HCN and NH 3 are also produced much more efficiently. We have applied the extended network to a simplified model of the accretion disk of an active galactic nucleus.

  17. Secure Distributed Databases Using Cryptography

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2006-01-01

    Full Text Available The computational encryption is used intensively by different databases management systems for ensuring privacy and integrity of information that are physically stored in files. Also, the information is sent over network and is replicated on different distributed systems. It is proved that a satisfying level of security is achieved if the rows and columns of tables are encrypted independently of table or computer that sustains the data. Also, it is very important that the SQL - Structured Query Language query requests and responses to be encrypted over the network connection between the client and databases server. All this techniques and methods must be implemented by the databases administrators, designer and developers in a consistent security policy.

  18. High temperature strength data-base of SUS304 steel and a study on life prediction method under ceep-fatigue interaction

    International Nuclear Information System (INIS)

    Matsubara, Masaaki; Nitta, Akito; Ogata, Takashi; Kuwabara, Kazuo

    1985-01-01

    As a part of ''Study for practical use of Tank Type FBR'', ''Practical use of inelastic analysis method to FBR structural design'' is carried out as a cooperative study for three years from 1984. In this cooperative study, to establish the life prediction method under creep-fatigue interaction is one of the most important theme. To attain this purpose, many different type tests are planned and then conducted. By the way, to use these many data rapidly and effectively, it is necessary to make a data base. So in this work, we developed the simple data base of high temperature strength. And the data of SUS304 obtained at this place to this day are inputted into this data base. Next, we investigated about five life prediction methods under creep-fatigue interaction, Frequency Modified Method, Ostergren Method, Strain Range Partitioning Method, Damage Rate Approach and Strain Energy Parameter Method. As a result, Strain Range Partitioning Method can predict the lives within Factor of 2. In the other four methods, it is supported that material constants in the prediction formula are dependent on temperature. (author)

  19. Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

    Science.gov (United States)

    Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

    2018-04-01

    We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

  20. Glass transition temperatures of microphase separated semi-interpenetrating polymer networks of polystyrene-inter-poly(cross)-2-ethylhexyl-methacrylate

    NARCIS (Netherlands)

    de Graaf, L.A.; de Graaf, Leontine A.; Möller, Martin; Moller, M.

    1995-01-01

    The glass transition temperature of semi-interpenetrating polymer networks (semi-IPNs) of atactic polystyrene (PS) in crosslinked methacrylates was studied by systematic variation of the morphology, that is domain size, continuity and concentration in the domains. Semi-IPNs were prepared from

  1. Development of multilayer perceptron networks for isothermal time temperature transformation prediction of U-Mo-X alloys

    Energy Technology Data Exchange (ETDEWEB)

    Johns, Jesse M., E-mail: jesse.johns@pnnl.gov; Burkes, Douglas, E-mail: douglas.burkes@pnnl.gov

    2017-07-15

    In this work, a multilayered perceptron (MLP) network is used to develop predictive isothermal time-temperature-transformation (TTT) models covering a range of U-Mo binary and ternary alloys. The selected ternary alloys for model development are U-Mo-Ru, U-Mo-Nb, U-Mo-Zr, U-Mo-Cr, and U-Mo-Re. These model's ability to predict 'novel' U-Mo alloys is shown quite well despite the discrepancies between literature sources for similar alloys which likely arise from different thermal-mechanical processing conditions. These models are developed with the primary purpose of informing experimental decisions. Additional experimental insight is necessary in order to reduce the number of experiments required to isolate ideal alloys. These models allow test planners to evaluate areas of experimental interest; once initial tests are conducted, the model can be updated and further improve follow-on testing decisions. The model also improves analysis capabilities by reducing the number of data points necessary from any particular test. For example, if one or two isotherms are measured during a test, the model can construct the rest of the TTT curve over a wide range of temperature and time. This modeling capability reduces the cost of experiments while also improving the value of the results from the tests. The reduced costs could result in improved material characterization and therefore improved fundamental understanding of TTT dynamics. As additional understanding of phenomena driving TTTs is acquired, this type of MLP model can be used to populate unknowns (such as material impurity and other thermal mechanical properties) from past literature sources.

  2. Predicting the effects of magnesium oxide nanoparticles and temperature on the thermal conductivity of water using artificial neural network and experimental data

    Science.gov (United States)

    Afrand, Masoud; Hemmat Esfe, Mohammad; Abedini, Ehsan; Teimouri, Hamid

    2017-03-01

    The current paper first presents an empirical correlation based on experimental results for estimating thermal conductivity enhancement of MgO-water nanofluid using curve fitting method. Then, artificial neural networks (ANNs) with various numbers of neurons have been assessed by considering temperature and MgO volume fraction as the inputs variables and thermal conductivity enhancement as the output variable to select the most appropriate and optimized network. Results indicated that the network with 7 neurons had minimum error. Eventually, the output of artificial neural network was compared with the results of the proposed empirical correlation and those of the experiments. Comparisons revealed that ANN modeling was more accurate than curve-fitting method in the predicting the thermal conductivity enhancement of the nanofluid.

  3. An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2014-02-01

    Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

  4. Database design using entity-relationship diagrams

    CERN Document Server

    Bagui, Sikha

    2011-01-01

    Data, Databases, and the Software Engineering ProcessDataBuilding a DatabaseWhat is the Software Engineering Process?Entity Relationship Diagrams and the Software Engineering Life Cycle          Phase 1: Get the Requirements for the Database          Phase 2: Specify the Database          Phase 3: Design the DatabaseData and Data ModelsFiles, Records, and Data ItemsMoving from 3 × 5 Cards to ComputersDatabase Models     The Hierarchical ModelThe Network ModelThe Relational ModelThe Relational Model and Functional DependenciesFundamental Relational DatabaseRelational Database and SetsFunctional

  5. NATIONAL TRANSPORTATION ATLAS DATABASE: RAILROADS 2011

    Data.gov (United States)

    Kansas Data Access and Support Center — The Rail Network is a comprehensive database of the nation's railway system at the 1:100,000 scale or better. The data set covers all 50 States plus the District of...

  6. Developmental and Reproductive Toxicology Database (DART)

    Data.gov (United States)

    U.S. Department of Health & Human Services — A bibliographic database on the National Library of Medicine's (NLM) Toxicology Data Network (TOXNET) with references to developmental and reproductive toxicology...

  7. Guide to the Durham-Rutherford high energy physics databases

    International Nuclear Information System (INIS)

    Gault, F.D.; Lotts, A.P.; Read, B.J.; Crawford, R.L.; Roberts, R.G.

    1979-12-01

    New databases and graphics facilities are added in this edition of the guide. It explains, with examples, how to retrieve tabulated experimental scattering data from databases on the Rutherford Laboratory computer network. (author)

  8. Database development and management

    CERN Document Server

    Chao, Lee

    2006-01-01

    Introduction to Database Systems Functions of a DatabaseDatabase Management SystemDatabase ComponentsDatabase Development ProcessConceptual Design and Data Modeling Introduction to Database Design Process Understanding Business ProcessEntity-Relationship Data Model Representing Business Process with Entity-RelationshipModelTable Structure and NormalizationIntroduction to TablesTable NormalizationTransforming Data Models to Relational Databases .DBMS Selection Transforming Data Models to Relational DatabasesEnforcing ConstraintsCreating Database for Business ProcessPhysical Design and Database

  9. An Adaptive Database Intrusion Detection System

    Science.gov (United States)

    Barrios, Rita M.

    2011-01-01

    Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent…

  10. The feasibility of retrieving vertical temperature profiles from satellite nadir UV observations: A sensitivity analysis and an inversion experiment with neural network algorithms

    International Nuclear Information System (INIS)

    Sellitto, P.; Del Frate, F.

    2014-01-01

    Atmospheric temperature profiles are inferred from passive satellite instruments, using thermal infrared or microwave observations. Here we investigate on the feasibility of the retrieval of height resolved temperature information in the ultraviolet spectral region. The temperature dependence of the absorption cross sections of ozone in the Huggins band, in particular in the interval 320–325 nm, is exploited. We carried out a sensitivity analysis and demonstrated that a non-negligible information on the temperature profile can be extracted from this small band. Starting from these results, we developed a neural network inversion algorithm, trained and tested with simulated nadir EnviSat-SCIAMACHY ultraviolet observations. The algorithm is able to retrieve the temperature profile with root mean square errors and biases comparable to existing retrieval schemes that use thermal infrared or microwave observations. This demonstrates, for the first time, the feasibility of temperature profiles retrieval from space-borne instruments operating in the ultraviolet. - Highlights: • A sensitivity analysis and an inversion scheme to retrieve temperature profiles from satellite UV observations (320–325 nm). • The exploitation of the temperature dependence of the absorption cross section of ozone in the Huggins band is proposed. • First demonstration of the feasibility of temperature profiles retrieval from satellite UV observations. • RMSEs and biases comparable with more established techniques involving TIR and MW observations

  11. Effect of the Network Structure and Programming Temperature on the Shape-Memory Response of Thiol-Epoxy “Click” Systems

    Directory of Open Access Journals (Sweden)

    Alberto Belmonte

    2015-10-01

    Full Text Available This paper presents a new methodology to develop “thiol-epoxy” shape-memory polymers (SMPs with enhanced mechanical properties in a simple and efficient manner via “click” chemistry by using thermal latent initiators. The shape-memory response (SMR, defined by the mechanical capabilities of the SMP (high ultimate strength and strain, the shape-fixation and the recovery of the original shape (shape-recovery, was analyzed on thiol-epoxy systems by varying the network structure and programming temperature. The glass transition temperature (Tg and crosslinking density were modified using 3- or 4- functional thiol curing agents and different amounts of a rigid triglycidyl isocyanurate compound. The relationship between the thermo-mechanical properties, network structure and the SMR was evidenced by means of qualitative and quantitative analysis. The influence of the programming temperature (Tprog on the SMR was also analyzed in detail. The results demonstrate the possibility of tailoring SMPs with enhanced mechanical capabilities and excellent SMR, and intend to provide a better insight into the relationship between the network structure properties, programming temperature and the SMR of unconstrained (stress-free systems; thus, making it easier to decide between different SMP and to define the operative parameters in the useful life.

  12. A Sandia telephone database system

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, S.D.; Tolendino, L.F.

    1991-08-01

    Sandia National Laboratories, Albuquerque, may soon have more responsibility for the operation of its own telephone system. The processes that constitute providing telephone service can all be improved through the use of a central data information system. We studied these processes, determined the requirements for a database system, then designed the first stages of a system that meets our needs for work order handling, trouble reporting, and ISDN hardware assignments. The design was based on an extensive set of applications that have been used for five years to manage the Sandia secure data network. The system utilizes an Ingres database management system and is programmed using the Application-By-Forms tools.

  13. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimise the management of the Technical Network (TN), to facilitate understanding of the purpose of devices connected to the TN and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive e-mails from IT/CS asking them to add the corresponding information in the network database at "network-cern-ch". Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  14. Long-term observations minus background monitoring of ground-based brightness temperatures from a microwave radiometer network

    Science.gov (United States)

    De Angelis, Francesco; Cimini, Domenico; Löhnert, Ulrich; Caumont, Olivier; Haefele, Alexander; Pospichal, Bernhard; Martinet, Pauline; Navas-Guzmán, Francisco; Klein-Baltink, Henk; Dupont, Jean-Charles; Hocking, James

    2017-10-01

    Ground-based microwave radiometers (MWRs) offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL) with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP) models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes) require an accurate representation of the differences between model (background) and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O-B). Monitoring of O-B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O-B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB) measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O-B monitoring can effectively detect instrument malfunctions. O-B statistics (bias, standard deviation, and root mean square) for water vapour channels (22.24-30.0 GHz) are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ˜ 2-2.5 K) towards the high-frequency wing ( ˜ 0.8-1.3 K). Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O-B statistics for temperature channels show different

  15. Mathematics for Databases

    NARCIS (Netherlands)

    ir. Sander van Laar

    2007-01-01

    A formal description of a database consists of the description of the relations (tables) of the database together with the constraints that must hold on the database. Furthermore the contents of a database can be retrieved using queries. These constraints and queries for databases can very well be

  16. Databases and their application

    NARCIS (Netherlands)

    Grimm, E.C.; Bradshaw, R.H.W; Brewer, S.; Flantua, S.; Giesecke, T.; Lézine, A.M.; Takahara, H.; Williams, J.W.,Jr; Elias, S.A.; Mock, C.J.

    2013-01-01

    During the past 20 years, several pollen database cooperatives have been established. These databases are now constituent databases of the Neotoma Paleoecology Database, a public domain, multiproxy, relational database designed for Quaternary-Pliocene fossil data and modern surface samples. The

  17. DOT Online Database

    Science.gov (United States)

    Page Home Table of Contents Contents Search Database Search Login Login Databases Advisory Circulars accessed by clicking below: Full-Text WebSearch Databases Database Records Date Advisory Circulars 2092 5 data collection and distribution policies. Document Database Website provided by MicroSearch

  18. Databases for INDUS-1 and INDUS-2

    International Nuclear Information System (INIS)

    Merh, Bhavna N.; Fatnani, Pravin

    2003-01-01

    The databases for Indus are relational databases designed to store various categories of data related to the accelerator. The data archiving and retrieving system in Indus is based on a client/sever model. A general purpose commercial database is used to store parameters and equipment data for the whole machine. The database manages configuration, on-line and historical databases. On line and off line applications distributed in several systems can store and retrieve the data from the database over the network. This paper describes the structure of databases for Indus-1 and Indus-2 and their integration within the software architecture. The data analysis, design, resulting data-schema and implementation issues are discussed. (author)

  19. Copolymer Networks From Oligo(ε-caprolactone) and n-Butyl Acrylate Enable a Reversible Bidirectional Shape-Memory Effect at Human Body Temperature.

    Science.gov (United States)

    Saatchi, Mersa; Behl, Marc; Nöchel, Ulrich; Lendlein, Andreas

    2015-05-01

    Exploiting the tremendous potential of the recently discovered reversible bidirectional shape-memory effect (rbSME) for biomedical applications requires switching temperatures in the physiological range. The recent strategy is based on the reduction of the melting temperature range (ΔT m ) of the actuating oligo(ε-caprolactone) (OCL) domains in copolymer networks from OCL and n-butyl acrylate (BA), where the reversible effect can be adjusted to the human body temperature. In addition, it is investigated whether an rbSME in the temperature range close or even above Tm,offset (end of the melting transition) can be obtained. Two series of networks having mixtures of OCLs reveal broad ΔTm s from 2 °C to 50 °C and from -10 °C to 37 °C, respectively. In cyclic, thermomechanical experiments the rbSME can be tailored to display pronounced actuation in a temperature interval between 20 °C and 37 °C. In this way, the application spectrum of the rbSME can be extended to biomedical applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Dietary Supplement Ingredient Database

    Science.gov (United States)

    ... and US Department of Agriculture Dietary Supplement Ingredient Database Toggle navigation Menu Home About DSID Mission Current ... values can be saved to build a small database or add to an existing database for national, ...

  1. Energy Consumption Database

    Science.gov (United States)

    Consumption Database The California Energy Commission has created this on-line database for informal reporting ) classifications. The database also provides easy downloading of energy consumption data into Microsoft Excel (XLSX

  2. Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide.

    Science.gov (United States)

    Tabaraki, R; Khayamian, T; Ensafi, A A

    2006-09-01

    A wavelet neural network (WNN) model in quantitative structure property relationship (QSPR) was developed for predicting solubility of 25 anthraquinone dyes in supercritical carbon dioxide over a wide range of pressures (70-770 bar) and temperatures (291-423 K). A large number of descriptors were calculated with Dragon software and a subset of calculated descriptors was selected from 18 classes of Dragon descriptors with a stepwise multiple linear regression (MLR) as a feature selection technique. Six calculated and two experimental descriptors, pressure and temperature, were selected as the most feasible descriptors. The selected descriptors were used as input nodes in a wavelet neural network (WNN) model. The wavelet neural network architecture and its parameters were optimized simultaneously. The data was randomly divided to the training, prediction and validation sets. The predictive ability of the model was evaluated using validation data set. The root mean squares error (RMSE) and mean absolute errors were 0.339 and 0.221, respectively, for the validation data set. The performance of the WNN model was also compared with artificial neural network (ANN) model and the results showed the superiority of the WNN over ANN model.

  3. Collecting Taxes Database

    Data.gov (United States)

    US Agency for International Development — The Collecting Taxes Database contains performance and structural indicators about national tax systems. The database contains quantitative revenue performance...

  4. USAID Anticorruption Projects Database

    Data.gov (United States)

    US Agency for International Development — The Anticorruption Projects Database (Database) includes information about USAID projects with anticorruption interventions implemented worldwide between 2007 and...

  5. NoSQL databases

    OpenAIRE

    Mrozek, Jakub

    2012-01-01

    This thesis deals with database systems referred to as NoSQL databases. In the second chapter, I explain basic terms and the theory of database systems. A short explanation is dedicated to database systems based on the relational data model and the SQL standardized query language. Chapter Three explains the concept and history of the NoSQL databases, and also presents database models, major features and the use of NoSQL databases in comparison with traditional database systems. In the fourth ...

  6. Secure Distributed Databases Using Cryptography

    OpenAIRE

    Ion IVAN; Cristian TOMA

    2006-01-01

    The computational encryption is used intensively by different databases management systems for ensuring privacy and integrity of information that are physically stored in files. Also, the information is sent over network and is replicated on different distributed systems. It is proved that a satisfying level of security is achieved if the rows and columns of tables are encrypted independently of table or computer that sustains the data. Also, it is very important that the SQL - Structured Que...

  7. Long-term observations minus background monitoring of ground-based brightness temperatures from a microwave radiometer network

    Directory of Open Access Journals (Sweden)

    F. De Angelis

    2017-10-01

    Full Text Available Ground-based microwave radiometers (MWRs offer the capability to provide continuous, high-temporal-resolution observations of the atmospheric thermodynamic state in the planetary boundary layer (PBL with low maintenance. This makes MWR an ideal instrument to supplement radiosonde and satellite observations when initializing numerical weather prediction (NWP models through data assimilation. State-of-the-art data assimilation systems (e.g. variational schemes require an accurate representation of the differences between model (background and observations, which are then weighted by their respective errors to provide the best analysis of the true atmospheric state. In this perspective, one source of information is contained in the statistics of the differences between observations and their background counterparts (O–B. Monitoring of O–B statistics is crucial to detect and remove systematic errors coming from the measurements, the observation operator, and/or the NWP model. This work illustrates a 1-year O–B analysis for MWR observations in clear-sky conditions for an European-wide network of six MWRs. Observations include MWR brightness temperatures (TB measured by the two most common types of MWR instruments. Background profiles are extracted from the French convective-scale model AROME-France before being converted into TB. The observation operator used to map atmospheric profiles into TB is the fast radiative transfer model RTTOV-gb. It is shown that O–B monitoring can effectively detect instrument malfunctions. O–B statistics (bias, standard deviation, and root mean square for water vapour channels (22.24–30.0 GHz are quite consistent for all the instrumental sites, decreasing from the 22.24 GHz line centre ( ∼  2–2.5 K towards the high-frequency wing ( ∼  0.8–1.3 K. Statistics for zenith and lower-elevation observations show a similar trend, though values increase with increasing air mass. O

  8. Prediction of the temperature of the atmosphere of the primary containment: comparison between neural networks and polynomial regression

    International Nuclear Information System (INIS)

    Alvarez Huerta, A.; Gonzalez Miguelez, R.; Garcia Metola, D.; Noriega Gonzalez, A.

    2011-01-01

    The modelization is carried out through two different techniques, a conventional polynomial regression and other based on an approach by neural networks artificial. He is a comparison between the quality of the forecast would make different models based on the polynomial regression and neural network with generalization by Bayesian regulation, using the indicators of the root of the mean square error and the coefficient of determination, in view of the results, the neural network generates a prediction more accurate and reliable than the polynomial regression.

  9. Modeling the Effects of Cu Content and Deformation Variables on the High-Temperature Flow Behavior of Dilute Al-Fe-Si Alloys Using an Artificial Neural Network.

    Science.gov (United States)

    Shakiba, Mohammad; Parson, Nick; Chen, X-Grant

    2016-06-30

    The hot deformation behavior of Al-0.12Fe-0.1Si alloys with varied amounts of Cu (0.002-0.31 wt %) was investigated by uniaxial compression tests conducted at different temperatures (400 °C-550 °C) and strain rates (0.01-10 s -1 ). The results demonstrated that flow stress decreased with increasing deformation temperature and decreasing strain rate, while flow stress increased with increasing Cu content for all deformation conditions studied due to the solute drag effect. Based on the experimental data, an artificial neural network (ANN) model was developed to study the relationship between chemical composition, deformation variables and high-temperature flow behavior. A three-layer feed-forward back-propagation artificial neural network with 20 neurons in a hidden layer was established in this study. The input parameters were Cu content, temperature, strain rate and strain, while the flow stress was the output. The performance of the proposed model was evaluated using the K-fold cross-validation method. The results showed excellent generalization capability of the developed model. Sensitivity analysis indicated that the strain rate is the most important parameter, while the Cu content exhibited a modest but significant influence on the flow stress.

  10. PrimateLit Database

    Science.gov (United States)

    Primate Info Net Related Databases NCRR PrimateLit: A bibliographic database for primatology Top of any problems with this service. We welcome your feedback. The PrimateLit database is no longer being Resources, National Institutes of Health. The database is a collaborative project of the Wisconsin Primate

  11. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimize the management of the Technical Network (TN), to ease the understanding and purpose of devices connected to the TN, and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive email notifications from IT/CS asking them to add the corresponding information in the network database. Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  12. KALIMER database development

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Kwan Seong; Lee, Yong Bum; Jeong, Hae Yong; Ha, Kwi Seok

    2003-03-01

    KALIMER database is an advanced database to utilize the integration management for liquid metal reactor design technology development using Web applications. KALIMER design database is composed of results database, Inter-Office Communication (IOC), 3D CAD database, and reserved documents database. Results database is a research results database during all phase for liquid metal reactor design technology development of mid-term and long-term nuclear R and D. IOC is a linkage control system inter sub project to share and integrate the research results for KALIMER. 3D CAD database is a schematic overview for KALIMER design structure. And reserved documents database is developed to manage several documents and reports since project accomplishment.

  13. KALIMER database development

    International Nuclear Information System (INIS)

    Jeong, Kwan Seong; Lee, Yong Bum; Jeong, Hae Yong; Ha, Kwi Seok

    2003-03-01

    KALIMER database is an advanced database to utilize the integration management for liquid metal reactor design technology development using Web applications. KALIMER design database is composed of results database, Inter-Office Communication (IOC), 3D CAD database, and reserved documents database. Results database is a research results database during all phase for liquid metal reactor design technology development of mid-term and long-term nuclear R and D. IOC is a linkage control system inter sub project to share and integrate the research results for KALIMER. 3D CAD database is a schematic overview for KALIMER design structure. And reserved documents database is developed to manage several documents and reports since project accomplishment

  14. Time response of temperature sensors using neural networks; Utilizacao de redes neurais artificiais para determinar o tempo de resposta de sensores de temperatura do tipo RTD

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Roberto Carlos dos

    2010-07-01

    In a PWR nuclear power plant, the primary coolant temperature and feedwater temperature are measured using RTDs (Resistance Temperature Detectors). These RTDs typically feed the plant's control and safety systems and must, therefore, be very accurate and have good dynamic performance. The response time of RTDs is characterized by a single parameter called the Plunge Time Constant defined as the time it takes the sensor output to achieve 63.2 percent of its final value after a step change in temperature. Nuclear reactor service conditions are difficult to reproduce in the laboratory, and an in-situ test method called LCSR (Loop Current Step Response) test was developed to measure remotely the response time of RTDs. >From this test, the time constant of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat-transfer model. This calculation is not simple and requires specialized personnel. For this reason an Artificial Neural Network has been developed to predict the time constant of RTD from LCSR test transient. It eliminates the transformations involved in the LCSR application. A series of LCSR tests on RTDs generates the response transients of the sensors, the input data of the networks. Plunge tests are used to determine the time constants of the RTDs, the desired output of the ANN, trained using these sets of input/output data. This methodology was firstly applied to theoretical data simulating 10 RTDs with different time constant values, resulting in an average error of about 0.74 %. Experimental data from three different RTDs was used to predict time constant resulting in a maximum error of 3,34 %. The time constants values predicted from ANN were compared with those obtained from traditional way resulting in an average error of about 18 % and that shows the network is able to predict accurately the sensor time constant. (author)

  15. Study on managing EPICS database using ORACLE

    International Nuclear Information System (INIS)

    Liu Shu; Wang Chunhong; Zhao Jijiu

    2007-01-01

    EPICS is used as a development toolkit of BEPCII control system. The core of EPICS is a distributed database residing in front-end machines. The distributed database is usually created by tools such as VDCT and text editor in the host, then loaded to front-end target IOCs through the network. In BEPCII control system there are about 20,000 signals, which are distributed in more than 20 IOCs. All the databases are developed by device control engineers using VDCT or text editor. There's no uniform tools providing transparent management. The paper firstly presents the current status on EPICS database management issues in many labs. Secondly, it studies EPICS database and the interface between ORACLE and EPICS database. finally, it introduces the software development and application is BEPCII control system. (authors)

  16. Logical database design principles

    CERN Document Server

    Garmany, John; Clark, Terry

    2005-01-01

    INTRODUCTION TO LOGICAL DATABASE DESIGNUnderstanding a Database Database Architectures Relational Databases Creating the Database System Development Life Cycle (SDLC)Systems Planning: Assessment and Feasibility System Analysis: RequirementsSystem Analysis: Requirements Checklist Models Tracking and Schedules Design Modeling Functional Decomposition DiagramData Flow Diagrams Data Dictionary Logical Structures and Decision Trees System Design: LogicalSYSTEM DESIGN AND IMPLEMENTATION The ER ApproachEntities and Entity Types Attribute Domains AttributesSet-Valued AttributesWeak Entities Constraint

  17. An Interoperable Cartographic Database

    OpenAIRE

    Slobodanka Ključanin; Zdravko Galić

    2007-01-01

    The concept of producing a prototype of interoperable cartographic database is explored in this paper, including the possibilities of integration of different geospatial data into the database management system and their visualization on the Internet. The implementation includes vectorization of the concept of a single map page, creation of the cartographic database in an object-relation database, spatial analysis, definition and visualization of the database content in the form of a map on t...

  18. Software listing: CHEMTOX database

    International Nuclear Information System (INIS)

    Moskowitz, P.D.

    1993-01-01

    Initially launched in 1983, the CHEMTOX Database was among the first microcomputer databases containing hazardous chemical information. The database is used in many industries and government agencies in more than 17 countries. Updated quarterly, the CHEMTOX Database provides detailed environmental and safety information on 7500-plus hazardous substances covered by dozens of regulatory and advisory sources. This brief listing describes the method of accessing data and provides ordering information for those wishing to obtain the CHEMTOX Database

  19. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  20. Determination of fat, moisture, and protein in meat and meat products by using the FOSS FoodScan Near-Infrared Spectrophotometer with FOSS Artificial Neural Network Calibration Model and Associated Database: collaborative study.

    Science.gov (United States)

    Anderson, Shirley

    2007-01-01

    A collaborative study was conducted to evaluate the repeatability and reproducibility of the FOSS FoodScan near-infrared spectrophotometer with artificial neural network calibration model and database for the determination of fat, moisture, and protein in meat and meat products. Representative samples were homogenized by grinding according to AOAC Official Method 983.18. Approximately 180 g ground sample was placed in a 140 mm round sample dish, and the dish was placed in the FoodScan. The operator ID was entered, the meat product profile within the software was selected, and the scanning process was initiated by pressing the "start" button. Results were displayed for percent (g/100 g) fat, moisture, and protein. Ten blind duplicate samples were sent to 15 collaborators in the United States. The within-laboratory (repeatability) relative standard deviation (RSD(r)) ranged from 0.22 to 2.67% for fat, 0.23 to 0.92% for moisture, and 0.35 to 2.13% for protein. The between-laboratories (reproducibility) relative standard deviation (RSD(R)) ranged from 0.52 to 6.89% for fat, 0.39 to 1.55% for moisture, and 0.54 to 5.23% for protein. The method is recommended for Official First Action.

  1. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    Science.gov (United States)

    Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

    2015-06-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

  2. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    International Nuclear Information System (INIS)

    Hosseini-Golgoo, S M; Bozorgi, H; Saberkari, A

    2015-01-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively. (paper)

  3. Thermodynamically Controlled High-Pressure High-Temperature Synthesis of Crystalline Fluorinated sp 3 -Carbon Networks

    Energy Technology Data Exchange (ETDEWEB)

    Klier, Kamil; Landskron, Kai

    2015-11-19

    We report the feasibility of the thermodynamically controlled synthesis of crystalline sp3-carbon networks. We show that there is a critical pressure below which decomposition of the carbon network is favored and above which the carbon network is stable. Based on advanced, highly accurate quantum mechanical calculations using the all-electron full-potential linearized augmented plane-wave method (FP-LAPW) and the Birch–Murnaghan equation of state, this critical pressure is 26.5 GPa (viz. table of contents graphic). Such pressures are experimentally readily accessible and afford thermodynamic control for suppression of decomposition reactions. The present results further suggest that a general pattern of pressure-directed control exists for many isolobal conversions of sp2 to sp3 allotropes, relating not only to fluorocarbon chemistry but also extending to inorganic and solid-state materials science.

  4. Effect of using of reclaimed asphalt and/or lower temperature asphalt on the availability of the road network

    NARCIS (Netherlands)

    Nicholls, C.; Wayman, M.; Mollenhauer, K.; McNally, C.; Tabakovic, A.; Varveri, A.; Cassidy, S.; Shahmohammadi, R.; Taylor, R.

    2015-01-01

    The use of reclaimed asphalt, secondary component materials and/or additives and lower temperature asphalt are being increasingly used in order to improve the sustainability of asphalt production. The use of reclaimed asphalt reduces the need for virgin materials whilst lower temperature asphalts

  5. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2016-10-14

    High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  6. Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules

    Directory of Open Access Journals (Sweden)

    Zhen Zhang

    2016-10-01

    Full Text Available High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial–temporal complexity. This paper presents a multi-input multi-output (MIMO self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional–integral–derivative (PID neural network (FCPIDNN and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

  7. Three-dimensional rigid multiphase networks providing high-temperature strength to cast AlSi10Cu5Ni1-2 piston alloys

    International Nuclear Information System (INIS)

    Asghar, Z.; Requena, G.; Boller, E.

    2011-01-01

    The three-dimensional (3-D) architecture of rigid multiphase networks present in AlSi10Cu5Ni1 and AlSi10Cu5Ni2 piston alloys in as-cast condition and after 4 h spheroidization treatment is characterized by synchrotron tomography in terms of the volume fraction of rigid phases, interconnectivity, contiguity and morphology. The architecture of both alloys consists of α-Al matrix and a rigid long-range 3-D network of Al 7 Cu 4 Ni, Al 4 Cu 2 Mg 8 Si 7 , Al 2 Cu, Al 15 Si 2 (FeMn) 3 and AlSiFeNiCu aluminides and Si. The investigated architectural parameters of both alloys studied are correlated with room-temperature and high-temperature (300 deg. C) strengths as a function of solution treatment time. The AlSi10Cu5Ni1 and AlSi10Cu5Ni2 alloys behave like metal matrix composites with 16 and 20 vol.% reinforcement, respectively. Both alloys have similar strengths in the as-cast condition, but the AlSi10Cu5Ni2 is able to retain ∼15% higher high temperature strength than the AlSi10Cu5Ni1 alloy after more than 4 h of spheroidization treatment. This is due to the preservation of the 3-D interconnectivity and the morphology of the rigid network, which is governed by the higher degree of contiguity between aluminides and Si.

  8. Thermodynamic Database for Zirconium Alloys

    International Nuclear Information System (INIS)

    Jerlerud Perez, Rosa

    2003-05-01

    For many decades zirconium alloys have been commonly used in the nuclear power industry as fuel cladding material. Besides their good corrosion resistance and acceptable mechanical properties the main reason of using these alloys is the low neutron absorption. Zirconium alloys are exposed to a very severe environment during the nuclear fission process and there is a demand for better design of this material. To meet this requirement a thermodynamic database is developed to support material designers. In this thesis some aspects about the development of a thermodynamic database for zirconium alloys are presented. A thermodynamic database represents an important facility in applying thermodynamic equilibrium calculations for a given material providing: 1) relevant information about the thermodynamic properties of the alloys e.g. enthalpies, activities, heat capacity, and 2) significant information for the manufacturing process e.g. heat treatment temperature. The basic information in the database is first the unary data, i.e. pure elements; those are taken from the compilation of the Scientific Group Thermodata Europe (SGTE) and then the binary and ternary systems. All phases present in those binary and ternary systems are described by means of the Gibbs energy dependence on composition and temperature. Many of those binary systems have been taken from published or unpublished works and others have been assessed in the present work. All the calculations have been made using Thermo C alc software and the representation of the Gibbs energy obtained by applying Calphad technique

  9. Developing wireless sensor networks for monitoring crop canopy temperature using a moving sprinkler system as a platform

    Science.gov (United States)

    The objectives of this study were to characterize wireless sensor nodes that we developed in terms of power consumption and functionality, and compare the performance of mesh and non-mesh wireless sensor networks (WSNs) comprised mainly of infrared thermometer thermocouples located on a center pivot...

  10. Little Cross-Feeding of the Mycorrhizal Networks Shared Between C3-Panicum bisulcatum and C4-Panicum maximum Under Different Temperature Regimes

    Directory of Open Access Journals (Sweden)

    Veronika Řezáčová

    2018-04-01

    Full Text Available Common mycorrhizal networks (CMNs formed by arbuscular mycorrhizal fungi (AMF interconnect plants of the same and/or different species, redistributing nutrients and draining carbon (C from the different plant partners at different rates. Here, we conducted a plant co-existence (intercropping experiment testing the role of AMF in resource sharing and exploitation by simplified plant communities composed of two congeneric grass species (Panicum spp. with different photosynthetic metabolism types (C3 or C4. The grasses had spatially separated rooting zones, conjoined through a root-free (but AMF-accessible zone added with 15N-labeled plant (clover residues. The plants were grown under two different temperature regimes: high temperature (36/32°C day/night or ambient temperature (25/21°C day/night applied over 49 days after an initial period of 26 days at ambient temperature. We made use of the distinct C-isotopic composition of the two plant species sharing the same CMN (composed of a synthetic AMF community of five fungal genera to estimate if the CMN was or was not fed preferentially under the specific environmental conditions by one or the other plant species. Using the C-isotopic composition of AMF-specific fatty acid (C16:1ω5 in roots and in the potting substrate harboring the extraradical AMF hyphae, we found that the C3-Panicum continued feeding the CMN at both temperatures with a significant and invariable share of C resources. This was surprising because the growth of the C3 plants was more susceptible to high temperature than that of the C4 plants and the C3-Panicum alone suppressed abundance of the AMF (particularly Funneliformis sp. in its roots due to the elevated temperature. Moreover, elevated temperature induced a shift in competition for nitrogen between the two plant species in favor of the C4-Panicum, as demonstrated by significantly lower 15N yields of the C3-Panicum but higher 15N yields of the C4-Panicum at elevated as

  11. A methodology of design for a one-variable neural network model to forecast the minimum temperature on the Mosquera zone, Cundimarca, Colombia

    International Nuclear Information System (INIS)

    Bonilla, Jose Ebert; Ramirez, Jairo; Ramirez, Oscar; Leon, Gloria and others

    2006-01-01

    The meteorological phenomena are factors that affect the economy, especially on a country like Colombia, which sustainability is based highly on agricultural products like corns, potato and flowers, plants of a paramour landscape like Bogota savannah. Among this phenomenon is the extreme minimum temperature (frost damage) it is a result of the non-lineal interactions of many atmospheric phenomena, for all that, frost damage forecast is very hard to accomplish with traditional methods. The approach of the project is to process this time series with an artificial neural network; it generals a now casting forecast on the zone of Mosquera

  12. Database Description - PSCDB | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available abase Description General information of database Database name PSCDB Alternative n...rial Science and Technology (AIST) Takayuki Amemiya E-mail: Database classification Structure Databases - Protein structure Database...554-D558. External Links: Original website information Database maintenance site Graduate School of Informat...available URL of Web services - Need for user registration Not available About This Database Database Descri...ption Download License Update History of This Database Site Policy | Contact Us Database Description - PSCDB | LSDB Archive ...

  13. Aspects of the design of distributed databases

    OpenAIRE

    Burlacu Irina-Andreea

    2011-01-01

    Distributed data - data, processed by a system, can be distributed among several computers, but it is accessible from any of them. A distributed database design problem is presented that involves the development of a global model, a fragmentation, and a data allocation. The student is given a conceptual entity-relationship model for the database and a description of the transactions and a generic network environment. A stepwise solution approach to this problem is shown, based on mean value a...

  14. Directory of IAEA databases

    International Nuclear Information System (INIS)

    1991-11-01

    The first edition of the Directory of IAEA Databases is intended to describe the computerized information sources available to IAEA staff members. It contains a listing of all databases produced at the IAEA, together with information on their availability

  15. Native Health Research Database

    Science.gov (United States)

    ... Indian Health Board) Welcome to the Native Health Database. Please enter your search terms. Basic Search Advanced ... To learn more about searching the Native Health Database, click here. Tutorial Video The NHD has made ...

  16. Cell Centred Database (CCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Cell Centered Database (CCDB) is a web accessible database for high resolution 2D, 3D and 4D data from light and electron microscopy, including correlated imaging.

  17. E3 Staff Database

    Data.gov (United States)

    US Agency for International Development — E3 Staff database is maintained by E3 PDMS (Professional Development & Management Services) office. The database is Mysql. It is manually updated by E3 staff as...

  18. Simultaneous influence of gas mixture composition and process temperature on Fe2O3->FeO reduction kinetics: neural network modeling

    Directory of Open Access Journals (Sweden)

    K. Piotrowski

    2005-09-01

    Full Text Available The kinetics of Fe2O3->FeO reaction was investigated. The thermogravimetric (TGA data covered the reduction of hematite both by pure species (nitrogen diluted CO or H2 and by their mixture. The conventional analysis has indicated that initially the reduction of hematite is a complex, surface controlled process, however once a thin layer of lower oxidation state iron oxides (magnetite, wüstite is formed on the surface, it changes to diffusion control. Artificial Neural Network (ANN has proved to be a convenient tool for modeling of this complex, heterogeneous reaction runs within the both (kinetic and diffusion regions, correctly considering influence of temperature and gas composition effects and their complex interactions. ANN's model shows the capability to mimic some extreme (minimum of the reaction rate within the determined temperature window, while the Arrhenius dependency is of limited use.

  19. NIRS database of the original research database

    International Nuclear Information System (INIS)

    Morita, Kyoko

    1991-01-01

    Recently, library staffs arranged and compiled the original research papers that have been written by researchers for 33 years since National Institute of Radiological Sciences (NIRS) established. This papers describes how the internal database of original research papers has been created. This is a small sample of hand-made database. This has been cumulating by staffs who have any knowledge about computer machine or computer programming. (author)

  20. Scopus database: a review.

    Science.gov (United States)

    Burnham, Judy F

    2006-03-08

    The Scopus database provides access to STM journal articles and the references included in those articles, allowing the searcher to search both forward and backward in time. The database can be used for collection development as well as for research. This review provides information on the key points of the database and compares it to Web of Science. Neither database is inclusive, but complements each other. If a library can only afford one, choice must be based in institutional needs.

  1. Aviation Safety Issues Database

    Science.gov (United States)

    Morello, Samuel A.; Ricks, Wendell R.

    2009-01-01

    The aviation safety issues database was instrumental in the refinement and substantiation of the National Aviation Safety Strategic Plan (NASSP). The issues database is a comprehensive set of issues from an extremely broad base of aviation functions, personnel, and vehicle categories, both nationally and internationally. Several aviation safety stakeholders such as the Commercial Aviation Safety Team (CAST) have already used the database. This broader interest was the genesis to making the database publically accessible and writing this report.

  2. Comparing between predicted output temperature of flat-plate solar collector and experimental results: computational fluid dynamics and artificial neural network

    Directory of Open Access Journals (Sweden)

    F Nadi

    2017-05-01

    Full Text Available Introduction The significant of solar energy as a renewable energy source, clean and without damage to the environment, for the production of electricity and heat is of great importance. Furthermore, due to the oil crisis as well as reducing the cost of home heating by 70%, solar energy in the past two decades has been a favorite of many researchers. Solar collectors are devices for collecting solar radiant energy through which this energy is converted into heat and then heat is transferred to a fluid (usually air or water. Therefore, a key component in performance improvement of solar heating system is a solar collector optimization under different testing conditions. However, estimation of output parameters under different testing conditions is costly, time consuming and mostly impossible. As a result, smart use of neural networks as well as CFD (computational fluid dynamics to predict the properties with which desired output would have been acquired is valuable. To the best of our knowledge, there are no any studies that compare experimental results with CFD and ANN. Materials and Methods A corrugated galvanized iron sheet of 2 m length, 1 m wide and 0.5 mm in thickness was used as an absorber plate for absorbing the incident solar radiation (Fig. 1 and 2. Corrugations in absorber were caused turbulent air and improved heat transfer coefficient. Computational fluid dynamics K-ε turbulence model was used for simulation. The following assumptions are made in the analysis. (1 Air is a continuous medium and incompressible. (2 The flow is steady and possesses have turbulent flow characteristics, due to the high velocity of flow. (3 The thermal-physical properties of the absorber sheet and the absorber tube are constant with respect to the operating temperature. (4 The bottom side of the absorber tube and the absorber plate are assumed to be adiabatic. Artificial neural network In this research a one-hidden-layer feed-forward network based on the

  3. Automated Oracle database testing

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    Ensuring database stability and steady performance in the modern world of agile computing is a major challenge. Various changes happening at any level of the computing infrastructure: OS parameters & packages, kernel versions, database parameters & patches, or even schema changes, all can potentially harm production services. This presentation shows how an automatic and regular testing of Oracle databases can be achieved in such agile environment.

  4. Inleiding database-systemen

    NARCIS (Netherlands)

    Pels, H.J.; Lans, van der R.F.; Pels, H.J.; Meersman, R.A.

    1993-01-01

    Dit artikel introduceert de voornaamste begrippen die een rol spelen rond databases en het geeft een overzicht van de doelstellingen, de functies en de componenten van database-systemen. Hoewel de functie van een database intuitief vrij duidelijk is, is het toch een in technologisch opzicht complex

  5. IAEA Illicit Trafficking Database (ITDB)

    International Nuclear Information System (INIS)

    2010-01-01

    The IAEA Illicit Trafficking Database (ITDB) was established in 1995 as a unique network of points of contact connecting 100 states and several international organizations. Information collected from official sources supplemented by open-source reports. The 1994 - GC 38, resolution intensifies the activities through which the Agency is currently supporting Member States in this field. Member states were notified of completed database in 1995 and invited to participate. The purpose of the I TDB is to facilitate exchange of authoritative information among States on incidents of illicit trafficking and other related unauthorized activities involving nuclear and other radioactive materials; to collect, maintain and analyse information on such incidents with a view to identifying common threats, trends, and patterns; use this information for internal planning and prioritisation and provide this information to member states and to provide a reliable source of basic information on such incidents to the media, when appropriate

  6. Temperature Scanning Stress Relaxation of an Autonomous Self-Healing Elastomer Containing Non-Covalent Reversible Network Junctions

    Directory of Open Access Journals (Sweden)

    Amit Das

    2018-01-01

    Full Text Available In this work, we report about the mechanical relaxation characteristics of an intrinsically self-healable imidazole modified commercial rubber. This kind of self-healing rubber was prepared by melt mixing of 1-butyl imidazole with bromo-butyl rubber (bromine modified isoprene-isobutylene copolymer, BIIR. By this melt mixing process, the reactive allylic bromine of bromo-butyl rubber was converted into imidazole bromide salt. The resulting development of an ionic character to the polymer backbone leads to an ionic association of the groups which ultimately results to the formation of a network structure of the rubber chains. The modified BIIR thus behaves like a robust crosslinked rubber and shows unusual self-healing properties. The non-covalent reversible network has been studied in detail with respect to stress relaxation experiments, scanning electron microscopic and X-ray scattering.

  7. Database Description - RMOS | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name RMOS Alternative nam...arch Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Microarray Data and other Gene Expression Database...s Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The Ric...19&lang=en Whole data download - Referenced database Rice Expression Database (RED) Rice full-length cDNA Database... (KOME) Rice Genome Integrated Map Database (INE) Rice Mutant Panel Database (Tos17) Rice Genome Annotation Database

  8. Predicting the co-melting temperatures of municipal solid waste incinerator fly ash and sewage sludge ash using grey model and neural network.

    Science.gov (United States)

    Pai, Tzu-Yi; Lin, Kae-Long; Shie, Je-Lung; Chang, Tien-Chin; Chen, Bor-Yann

    2011-03-01

    A grey model (GM) and an artificial neural network (ANN) were employed to predict co-melting temperature of municipal solid waste incinerator (MSWI) fly ash and sewage sludge ash (SSA) during formation of modified slag. The results indicated that in the aspect of model prediction, the mean absolute percentage error (MAPEs) were between 1.69 and 13.20% when adopting seven different GM (1, N) models. The MAPE were 1.59 and 1.31% when GM (1, 1) and rolling grey model (RGM (1, 1)) were adopted. The MAPEs fell within the range of 0.04 and 0.50% using different types of ANN. In GMs, the MAPE of 1.31% was found to be the lowest when using RGM (1, 1) to predict co-melting temperature. This value was higher than those of ANN2-1 to ANN8-1 by 1.27, 1.25, 1.24, 1.18, 1.16, 1.14 and 0.81%, respectively. GM only required a small amount of data (at least four data). Therefore, GM could be applied successfully in predicting the co-melting temperature of MSWI fly ash and SSA when no sufficient information is available. It also indicates that both the composition of MSWI fly ash and SSA could be applied on the prediction of co-melting temperature.

  9. Room temperature, ppb-level NO2 gas sensing of multiple-networked ZnSe nanowire sensors under UV illumination

    Directory of Open Access Journals (Sweden)

    Sunghoon Park

    2014-10-01

    Full Text Available Reports of the gas sensing properties of ZnSe are few, presumably because of the decomposition and oxidation of ZnSe at high temperatures. In this study, ZnSe nanowires were synthesized by the thermal evaporation of ZnSe powders and the sensing performance of multiple-networked ZnSe nanowire sensors toward NO2 gas was examined. The results showed that ZnSe might be a promising gas sensor material if it is used at room temperature. The response of the ZnSe nanowires to 50 ppb–5 ppm NO2 at room temperature under dark and UV illumination conditions were 101–102% and 113–234%, respectively. The responses of the ZnSe nanowires to 5 ppm NO2 increased from 102 to 234% with increasing UV illumination intensity from 0 to 1.2 mW/cm2. The response of the ZnSe nanowires was stronger than or comparable to that of typical metal oxide semiconductors reported in the literature, which require higher NO2 concentrations and operate at higher temperatures. The origin of the enhanced response of the ZnSe nanowires towards NO2 under UV illumination is also discussed.

  10. Concurrency control in distributed database systems

    CERN Document Server

    Cellary, W; Gelenbe, E

    1989-01-01

    Distributed Database Systems (DDBS) may be defined as integrated database systems composed of autonomous local databases, geographically distributed and interconnected by a computer network.The purpose of this monograph is to present DDBS concurrency control algorithms and their related performance issues. The most recent results have been taken into consideration. A detailed analysis and selection of these results has been made so as to include those which will promote applications and progress in the field. The application of the methods and algorithms presented is not limited to DDBSs but a

  11. Development of rubber mixing process mathematical model and synthesis of control correction algorithm by process temperature mode using an artificial neural network

    Directory of Open Access Journals (Sweden)

    V. S. Kudryashov

    2016-01-01

    Full Text Available The article is devoted to the development of a correction control algorithm by temperature mode of a periodic rubber mixing process for JSC "Voronezh tire plant". The algorithm is designed to perform in the main controller a section of rubber mixing Siemens S7 CPU319F-3 PN/DP, which forms tasks for the local temperature controllers HESCH HE086 and Jumo dTRON304, operating by tempering stations. To compile the algorithm was performed a systematic analysis of rubber mixing process as an object of control and was developed a mathematical model of the process based on the heat balance equations describing the processes of heat transfer through the walls of technological devices, the change of coolant temperature and the temperature of the rubber compound mixing until discharge from the mixer chamber. Due to the complexity and nonlinearity of the control object – Rubber mixers and the availability of methods and a wide experience of this device control in an industrial environment, a correction algorithm is implemented on the basis of an artificial single-layer neural network and it provides the correction of tasks for local controllers on the cooling water temperature and air temperature in the workshop, which may vary considerably depending on the time of the year, and during prolonged operation of the equipment or its downtime. Tempering stations control is carried out by changing the flow of cold water from the cooler and on/off control of the heating elements. The analysis of the model experiments results and practical research at the main controller programming in the STEP 7 environment at the enterprise showed a decrease in the mixing time for different types of rubbers by reducing of heat transfer process control error.

  12. An Interoperable Cartographic Database

    Directory of Open Access Journals (Sweden)

    Slobodanka Ključanin

    2007-05-01

    Full Text Available The concept of producing a prototype of interoperable cartographic database is explored in this paper, including the possibilities of integration of different geospatial data into the database management system and their visualization on the Internet. The implementation includes vectorization of the concept of a single map page, creation of the cartographic database in an object-relation database, spatial analysis, definition and visualization of the database content in the form of a map on the Internet. 

  13. Keyword Search in Databases

    CERN Document Server

    Yu, Jeffrey Xu; Chang, Lijun

    2009-01-01

    It has become highly desirable to provide users with flexible ways to query/search information over databases as simple as keyword search like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information among objects in a database using a set of keywords. Such structural information to be returned can be either trees or subgraphs representing how the objects, that contain the required keywords, are interconnected in a relational database or in an XML database. The structural keyword search is completely different from

  14. Nuclear power economic database

    International Nuclear Information System (INIS)

    Ding Xiaoming; Li Lin; Zhao Shiping

    1996-01-01

    Nuclear power economic database (NPEDB), based on ORACLE V6.0, consists of three parts, i.e., economic data base of nuclear power station, economic data base of nuclear fuel cycle and economic database of nuclear power planning and nuclear environment. Economic database of nuclear power station includes data of general economics, technique, capital cost and benefit, etc. Economic database of nuclear fuel cycle includes data of technique and nuclear fuel price. Economic database of nuclear power planning and nuclear environment includes data of energy history, forecast, energy balance, electric power and energy facilities

  15. Interconnecting heterogeneous database management systems

    Science.gov (United States)

    Gligor, V. D.; Luckenbaugh, G. L.

    1984-01-01

    It is pointed out that there is still a great need for the development of improved communication between remote, heterogeneous database management systems (DBMS). Problems regarding the effective communication between distributed DBMSs are primarily related to significant differences between local data managers, local data models and representations, and local transaction managers. A system of interconnected DBMSs which exhibit such differences is called a network of distributed, heterogeneous DBMSs. In order to achieve effective interconnection of remote, heterogeneous DBMSs, the users must have uniform, integrated access to the different DBMs. The present investigation is mainly concerned with an analysis of the existing approaches to interconnecting heterogeneous DBMSs, taking into account four experimental DBMS projects.

  16. Temperature Sensor Feasibility Study of Wireless Sensor Network Applications for Heating Efficiency Maintenance in High-Rise Apartment Buildings

    Directory of Open Access Journals (Sweden)

    Freliha B.

    2015-06-01

    Full Text Available Cities are responsible for 60%-80% of the world’s energy use and for approximately the same percentage of greenhouse gas emissions. The existing multi-apartment buildings of multifamily housing sector are often energy inefficient, and the heating system does not ensure optimization of heat distribution of individual apartments. Heat distribution, heating system balancing, heat loss detection and calculation, individual heat energy accounting are difficult tasks to accomplish. This article deals with the temperature monitoring system designed to retrieve temperature differences necessary for overall building heat monitoring and individual apartment monitoring. The sensor testing case study process and its measurements are analysed.

  17. Database Description - RPD | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available ase Description General information of database Database name RPD Alternative name Rice Proteome Database...titute of Crop Science, National Agriculture and Food Research Organization Setsuko Komatsu E-mail: Database... classification Proteomics Resources Plant databases - Rice Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database... description Rice Proteome Database contains information on protei...and entered in the Rice Proteome Database. The database is searchable by keyword,

  18. Database Description - JSNP | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name JSNP Alternative nam...n Science and Technology Agency Creator Affiliation: Contact address E-mail : Database...sapiens Taxonomy ID: 9606 Database description A database of about 197,000 polymorphisms in Japanese populat...1):605-610 External Links: Original website information Database maintenance site Institute of Medical Scien...er registration Not available About This Database Database Description Download License Update History of This Database

  19. Database Description - ASTRA | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available abase Description General information of database Database name ASTRA Alternative n...tics Journal Search: Contact address Database classification Nucleotide Sequence Databases - Gene structure,...3702 Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The database represents classified p...(10):1211-6. External Links: Original website information Database maintenance site National Institute of Ad... for user registration Not available About This Database Database Description Dow

  20. Database Description - RED | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available ase Description General information of database Database name RED Alternative name Rice Expression Database...enome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Database classifi...cation Microarray, Gene Expression Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database descripti... Article title: Rice Expression Database: the gateway to rice functional genomics...nt Science (2002) Dec 7 (12):563-564 External Links: Original website information Database maintenance site

  1. Database Description - PLACE | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available abase Description General information of database Database name PLACE Alternative name A Database...Kannondai, Tsukuba, Ibaraki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Databas...e classification Plant databases Organism Taxonomy Name: Tracheophyta Taxonomy ID: 58023 Database...99, Vol.27, No.1 :297-300 External Links: Original website information Database maintenance site National In...- Need for user registration Not available About This Database Database Descripti

  2. Data mining the EXFOR database

    International Nuclear Information System (INIS)

    Brown, David; Herman, Michal; Hirdt, John

    2014-01-01

    The EXFOR database contains the largest collection of experimental nuclear reaction data available as well as this data's bibliographic information and experimental details. We created an undirected graph from the EXFOR datasets with graph nodes representing single observables and graph links representing the connections of various types between these observables. This graph is an abstract representation of the connections in EXFOR, similar to graphs of social networks, authorship networks, etc. Analysing this abstract graph, we are able to address very specific questions such as: i) What observables are being used as reference measurements by the experimental community? ii) Are these observables given the attention needed by various standards organisations? iii) Are there classes of observables that are not connected to these reference measurements? In addressing these questions, we propose several (mostly cross-section) observables that should be evaluated and made into reaction reference standards. (authors)

  3. Database Description - Arabidopsis Phenome Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Arabidopsis Phenome Database Database Description General information of database Database n... BioResource Center Hiroshi Masuya Database classification Plant databases - Arabidopsis thaliana Organism T...axonomy Name: Arabidopsis thaliana Taxonomy ID: 3702 Database description The Arabidopsis thaliana phenome i...heir effective application. We developed the new Arabidopsis Phenome Database integrating two novel database...seful materials for their experimental research. The other, the “Database of Curated Plant Phenome” focusing

  4. Electroabsorption modulator laser for cost-effective 40 Gbit/s networks with low drive voltage, chirp and temperature dependence

    DEFF Research Database (Denmark)

    Aubin, G.; Seoane, Jorge; Merghem, K.

    2009-01-01

    The performances of a novel low-chirp electroabsorption modulator laser module are presented. Transmission is analysed in standard singlermode fibre at 40 Gbit/s. Propagation without chromatic dispersion compensation up to 2 km exhibits a low penalty variation over a wide temperature range. A pro....... A propagation scheme with compensation leads to negligible impairment at 88 km....

  5. Effects of Ceramic Density and Sintering Temperature on the Mechanical Properties of a Novel Polymer-Infiltrated Ceramic-Network Zirconia Dental Restorative (Filling) Material.

    Science.gov (United States)

    Li, Weiyan; Sun, Jian

    2018-05-10

    BACKGROUND Polymer-infiltrated ceramic-network (PICN) dental material is a new and practical development in orthodontics. Sintering is the process of forming a stable solid mass from a powder by heating without melting. The aim of this study was to evaluate the effects of sintering temperature on the mechanical properties of a PICN zirconia dental material. MATERIAL AND METHODS A dense zirconia ceramic and four PICN zirconia dental materials, with varying porosities, were sintered at three different temperatures; 12 PICN zirconia dental materials based on these porous ceramics were prepared, as well as a pure polymer. After the specimen preparation, flexural strength and elastic modulus values were measured using the three-point bending test, and fracture toughness were determined by the single-edge notched beam (SENB) method. The Vickers hardness test method was used with an indentation strength (IS) test. Scanning electron microscopy (SEM) was used to examine the microstructure of the ceramic surface and the fracture surface. RESULTS Mechanical properties of the PICN dental materials, including flexural strength, elastic modulus, fracture toughness, and hardness, were more similar to the properties of natural teeth when compared with traditional dental ceramic materials, and were affected by the density and sintering temperature. SEM showed that the porous ceramic network became cohesive and that the length of cracks in the PICN dental material was reduced. CONCLUSIONS PICN zirconia dental materials were characterized by similar mechanical properties to natural dental tissues, but further studies are required continue to improve the similarities with natural human enamel and dentin.

  6. Experience in running relational databases on clustered storage

    CERN Document Server

    Aparicio, Ruben Gaspar

    2015-01-01

    For past eight years, CERN IT Database group has based its backend storage on NAS (Network-Attached Storage) architecture, providing database access via NFS (Network File System) protocol. In last two and half years, our storage has evolved from a scale-up architecture to a scale-out one. This paper describes our setup and a set of functionalities providing key features to other services like Database on Demand [1] or CERN Oracle backup and recovery service. It also outlines possible trend of evolution that, storage for databases could follow.

  7. Hazard Analysis Database Report

    CERN Document Server

    Grams, W H

    2000-01-01

    The Hazard Analysis Database was developed in conjunction with the hazard analysis activities conducted in accordance with DOE-STD-3009-94, Preparation Guide for U S . Department of Energy Nonreactor Nuclear Facility Safety Analysis Reports, for HNF-SD-WM-SAR-067, Tank Farms Final Safety Analysis Report (FSAR). The FSAR is part of the approved Authorization Basis (AB) for the River Protection Project (RPP). This document describes, identifies, and defines the contents and structure of the Tank Farms FSAR Hazard Analysis Database and documents the configuration control changes made to the database. The Hazard Analysis Database contains the collection of information generated during the initial hazard evaluations and the subsequent hazard and accident analysis activities. The Hazard Analysis Database supports the preparation of Chapters 3 ,4 , and 5 of the Tank Farms FSAR and the Unreviewed Safety Question (USQ) process and consists of two major, interrelated data sets: (1) Hazard Analysis Database: Data from t...

  8. Database Optimizing Services

    Directory of Open Access Journals (Sweden)

    Adrian GHENCEA

    2010-12-01

    Full Text Available Almost every organization has at its centre a database. The database provides support for conducting different activities, whether it is production, sales and marketing or internal operations. Every day, a database is accessed for help in strategic decisions. The satisfaction therefore of such needs is entailed with a high quality security and availability. Those needs can be realised using a DBMS (Database Management System which is, in fact, software for a database. Technically speaking, it is software which uses a standard method of cataloguing, recovery, and running different data queries. DBMS manages the input data, organizes it, and provides ways of modifying or extracting the data by its users or other programs. Managing the database is an operation that requires periodical updates, optimizing and monitoring.

  9. National Database of Geriatrics

    DEFF Research Database (Denmark)

    Kannegaard, Pia Nimann; Vinding, Kirsten L; Hare-Bruun, Helle

    2016-01-01

    AIM OF DATABASE: The aim of the National Database of Geriatrics is to monitor the quality of interdisciplinary diagnostics and treatment of patients admitted to a geriatric hospital unit. STUDY POPULATION: The database population consists of patients who were admitted to a geriatric hospital unit....... Geriatric patients cannot be defined by specific diagnoses. A geriatric patient is typically a frail multimorbid elderly patient with decreasing functional ability and social challenges. The database includes 14-15,000 admissions per year, and the database completeness has been stable at 90% during the past......, percentage of discharges with a rehabilitation plan, and the part of cases where an interdisciplinary conference has taken place. Data are recorded by doctors, nurses, and therapists in a database and linked to the Danish National Patient Register. DESCRIPTIVE DATA: Descriptive patient-related data include...

  10. FY 1998 annual summary report on International Clean Energy Network Using Hydrogen Conversion (WE-NET) system technology. Subtask 6. Development of cryogenic temperature materials technologies; 1998 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 6 (teion zairyo gijutsu no kaihatsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

    Summarized herein are the cryogenic temperature materials technologies for the International Clean Energy Network Using Hydrogen Conversion (WE-NET) project, developed in FY 1998. The R and D programs have been implemented continuously since 1994. For stainless steel, the base and TIG weld metals were evaluated for their material characteristics in liquid hydrogen. The items investigated included the influences of hydrogen charge, 20% of stretch working on the base metal, welding methods, and ?-ferrite content on the characteristics. Fatigue strength of the base metal was found to increases as temperature decreases, but remain unchanged in a range from 20 to 77K. No significant difference was observed between 304L and 316L. For aluminum alloy, mechanical characteristics, centered by fatigue characteristics, were investigated for the base and weld metals. The sample of higher tensile strength showed a higher fatigue strength, at room temperature, 77 and 4K. The other tested items investigated included embrittlement characteristics in a hydrogen atmosphere, phase transformation, hydrogen diffusion and fracture toughness, for establishing the databases of cryogenic temperature materials. (NEDO)

  11. Specialist Bibliographic Databases

    OpenAIRE

    Gasparyan, Armen Yuri; Yessirkepov, Marlen; Voronov, Alexander A.; Trukhachev, Vladimir I.; Kostyukova, Elena I.; Gerasimov, Alexey N.; Kitas, George D.

    2016-01-01

    Specialist bibliographic databases offer essential online tools for researchers and authors who work on specific subjects and perform comprehensive and systematic syntheses of evidence. This article presents examples of the established specialist databases, which may be of interest to those engaged in multidisciplinary science communication. Access to most specialist databases is through subscription schemes and membership in professional associations. Several aggregators of information and d...

  12. Supply Chain Initiatives Database

    Energy Technology Data Exchange (ETDEWEB)

    None

    2012-11-01

    The Supply Chain Initiatives Database (SCID) presents innovative approaches to engaging industrial suppliers in efforts to save energy, increase productivity and improve environmental performance. This comprehensive and freely-accessible database was developed by the Institute for Industrial Productivity (IIP). IIP acknowledges Ecofys for their valuable contributions. The database contains case studies searchable according to the types of activities buyers are undertaking to motivate suppliers, target sector, organization leading the initiative, and program or partnership linkages.

  13. Foundations of database systems : an introductory tutorial

    NARCIS (Netherlands)

    Paredaens, J.; Paredaens, J.; Tenenbaum, L. A.

    1994-01-01

    A very short overview is given of the principles of databases. The entity relationship model is used to define the conceptual base. Furthermore file management, the hierarchical model, the network model, the relational model and the object oriented model are discussed During the second world war,

  14. Database setup insuring radiopharmaceuticals traceability

    International Nuclear Information System (INIS)

    Robert, N.; Salmon, F.; Clermont-Gallerande, H. de; Celerier, C.

    2002-01-01

    Having to organize radiopharmacy and to insure proper traceability of radiopharmaceutical medicines brings numerous problems, especially for the departments which are not assisted with global management network systems. Our work has been to find a solution enabling to use high street software to cover those needs. We have set up a PC database run by the Microsoft software ACCESS 97. Its use consists in: saving data related to generators, isotopes and kits reception and deletion, as well as the results of quality control; transferring data collected from the software that is connected to the activimeter (elutions and preparations registers, prescription book). By relating all the saved data, ACCESS enables to mix all information in order to proceed requests. At this stage, it is possible to edit all regular registers (prescription book, generator and radionuclides follow-up, blood derived medicines traceability) and to quickly retrieve patients who have received a particular radiopharmaceutical, or the radiopharmaceutical that has been given to a particular patient. This user-friendly database provides a considerable support to nuclear medicine department that don't possess any network management for their radiopharmaceutical activity. (author)

  15. Database Description - SAHG | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name SAHG Alternative nam...h: Contact address Chie Motono Tel : +81-3-3599-8067 E-mail : Database classification Structure Databases - ...e databases - Protein properties Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description... Links: Original website information Database maintenance site The Molecular Profiling Research Center for D...stration Not available About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Database Description - SAHG | LSDB Archive ...

  16. Intermodal Passenger Connectivity Database -

    Data.gov (United States)

    Department of Transportation — The Intermodal Passenger Connectivity Database (IPCD) is a nationwide data table of passenger transportation terminals, with data on the availability of connections...

  17. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  18. Residency Allocation Database

    Data.gov (United States)

    Department of Veterans Affairs — The Residency Allocation Database is used to determine allocation of funds for residency programs offered by Veterans Affairs Medical Centers (VAMCs). Information...

  19. Smart Location Database - Service

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Smart Location Database (SLD) summarizes over 80 demographic, built environment, transit service, and destination accessibility attributes for every census block...

  20. Database principles programming performance

    CERN Document Server

    O'Neil, Patrick

    2014-01-01

    Database: Principles Programming Performance provides an introduction to the fundamental principles of database systems. This book focuses on database programming and the relationships between principles, programming, and performance.Organized into 10 chapters, this book begins with an overview of database design principles and presents a comprehensive introduction to the concepts used by a DBA. This text then provides grounding in many abstract concepts of the relational model. Other chapters introduce SQL, describing its capabilities and covering the statements and functions of the programmi

  1. Veterans Administration Databases

    Science.gov (United States)

    The Veterans Administration Information Resource Center provides database and informatics experts, customer service, expert advice, information products, and web technology to VA researchers and others.

  2. IVR EFP Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This database contains trip-level reports submitted by vessels participating in Exempted Fishery projects with IVR reporting requirements.

  3. Towards Sensor Database Systems

    DEFF Research Database (Denmark)

    Bonnet, Philippe; Gehrke, Johannes; Seshadri, Praveen

    2001-01-01

    . These systems lack flexibility because data is extracted in a predefined way; also, they do not scale to a large number of devices because large volumes of raw data are transferred regardless of the queries that are submitted. In our new concept of sensor database system, queries dictate which data is extracted...... from the sensors. In this paper, we define the concept of sensor databases mixing stored data represented as relations and sensor data represented as time series. Each long-running query formulated over a sensor database defines a persistent view, which is maintained during a given time interval. We...... also describe the design and implementation of the COUGAR sensor database system....

  4. Database Publication Practices

    DEFF Research Database (Denmark)

    Bernstein, P.A.; DeWitt, D.; Heuer, A.

    2005-01-01

    There has been a growing interest in improving the publication processes for database research papers. This panel reports on recent changes in those processes and presents an initial cut at historical data for the VLDB Journal and ACM Transactions on Database Systems.......There has been a growing interest in improving the publication processes for database research papers. This panel reports on recent changes in those processes and presents an initial cut at historical data for the VLDB Journal and ACM Transactions on Database Systems....

  5. Smart Location Database - Download

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Smart Location Database (SLD) summarizes over 80 demographic, built environment, transit service, and destination accessibility attributes for every census block...

  6. Database Description - RMG | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available ase Description General information of database Database name RMG Alternative name ...raki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Database... classification Nucleotide Sequence Databases Organism Taxonomy Name: Oryza sativa Japonica Group Taxonomy ID: 39947 Database...rnal: Mol Genet Genomics (2002) 268: 434–445 External Links: Original website information Database...available URL of Web services - Need for user registration Not available About This Database Database Descri

  7. Database Description - KOME | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available base Description General information of database Database name KOME Alternative nam... Sciences Plant Genome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice ...Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description Information about approximately ...Hayashizaki Y, Kikuchi S. Journal: PLoS One. 2007 Nov 28; 2(11):e1235. External Links: Original website information Database...OS) Rice mutant panel database (Tos17) A Database of Plant Cis-acting Regulatory

  8. Update History of This Database - Arabidopsis Phenome Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Arabidopsis Phenome Database Update History of This Database Date Update contents 2017/02/27 Arabidopsis Phenome Data...base English archive site is opened. - Arabidopsis Phenome Database (http://jphenom...e.info/?page_id=95) is opened. About This Database Database Description Download License Update History of This Database... Site Policy | Contact Us Update History of This Database - Arabidopsis Phenome Database | LSDB Archive ...

  9. Update History of This Database - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us SKIP Stemcell Database Update History of This Database Date Update contents 2017/03/13 SKIP Stemcell Database... English archive site is opened. 2013/03/29 SKIP Stemcell Database ( https://www.skip.med.k...eio.ac.jp/SKIPSearch/top?lang=en ) is opened. About This Database Database Description Download License Update History of This Databa...se Site Policy | Contact Us Update History of This Database - SKIP Stemcell Database | LSDB Archive ...

  10. Update History of This Database - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Yeast Interacting Proteins Database Update History of This Database Date Update contents 201...0/03/29 Yeast Interacting Proteins Database English archive site is opened. 2000/12/4 Yeast Interacting Proteins Database...( http://itolab.cb.k.u-tokyo.ac.jp/Y2H/ ) is released. About This Database Database Description... Download License Update History of This Database Site Policy | Contact Us Update History of This Database... - Yeast Interacting Proteins Database | LSDB Archive ...

  11. Wavelet-based multi-resolution analysis and artificial neural networks for forecasting temperature and thermal power consumption

    OpenAIRE

    Eynard , Julien; Grieu , Stéphane; Polit , Monique

    2011-01-01

    15 pages; International audience; As part of the OptiEnR research project, the present paper deals with outdoor temperature and thermal power consumption forecasting. This project focuses on optimizing the functioning of a multi-energy district boiler (La Rochelle, west coast of France), adding to the plant a thermal storage unit and implementing a model-based predictive controller. The proposed short-term forecast method is based on the concept of time series and uses both a wavelet-based mu...

  12. Download - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Trypanosomes Database Download First of all, please read the license of this database. Data ...1.4 KB) Simple search and download Downlaod via FTP FTP server is sometimes jammed. If it is, access [here]. About This Database Data...base Description Download License Update History of This Database Site Policy | Contact Us Download - Trypanosomes Database | LSDB Archive ...

  13. Database design and database administration for a kindergarten

    OpenAIRE

    Vítek, Daniel

    2009-01-01

    The bachelor thesis deals with creation of database design for a standard kindergarten, installation of the designed database into the database system Oracle Database 10g Express Edition and demonstration of the administration tasks in this database system. The verification of the database was proved by a developed access application.

  14. CMS experience with online and offline Databases

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The CMS experiment is made of many detectors which in total sum up to more than 75 million channels. The online database stores the configuration data used to configure the various parts of the detector and bring it in all possible running states. The database also stores the conditions data, detector monitoring parameters of all channels (temperatures, voltages), detector quality information, beam conditions, etc. These quantities are used by the experts to monitor the detector performance in detail, as they occupy a very large space in the online database they cannot be used as-is for offline data reconstruction. For this, a "condensed" set of the full information, the "conditions data", is created and copied to a separate database used in the offline reconstruction. The offline conditions database contains the alignment and calibrations data for the various detectors. Conditions data sets are accessed by a tag and an interval of validity through the offline reconstruction program CMSSW, written in C++. Pe...

  15. Prediction by artificial neural networks of the physicochemical quality of cane molasses vinegar by time-temperature effect of food to flash evaporator-distiller

    Directory of Open Access Journals (Sweden)

    Víctor Vásquez V

    2010-03-01

    Full Text Available It was predicted via Artificial Neural Networks (ANN important physicochemical characteristics of molasses vinegar: pH, density, total acidity, ethanol, total aldehydes and furfural, obtained by flash evaporation operations and flash distillation clarification. Alcoholic and acetic fermented molasses were fed to a flash evaporator at four temperatures (61, 66, 71 and 76 ° C and in three times (25, 35 and 45 min. The prediction was made with two networks: ANN and ANN-A-B, both with good performance. The ANN-A was of the feedforward (FF type with Backpropagation (BP training algorithms and set of Levenberg-Marquardt (LM weights adjustment, topology: 6 inputs (operations data of flash evaporation-distillation, 7 linear outputs (physicochemical characteristics, 9 tangent sigmoidal neurons in 1 hidden layer, 0.5 moment coefficient, 0.01 learning rate, 0.0001 error goal and 20 training stages. The ANN-A showed better performance than a statistical model of first order. The ANN-B also FF, BP and LM algorithms, topology: 2 inputs (data from flash evaporation, 7 linear outputs (physical and chemical characteristics, 84 logarithm sigmoid neurons in 1 hidden layer, 0.5 moment coefficient, 0.01 learning rate, 0.0001 error goal and 300 training stages. The ANN-B showed the same predictive capacity as a statistical model of the first-order with interaction of terms.

  16. Directory of IAEA databases

    International Nuclear Information System (INIS)

    1992-12-01

    This second edition of the Directory of IAEA Databases has been prepared within the Division of Scientific and Technical Information (NESI). Its main objective is to describe the computerized information sources available to staff members. This directory contains all databases produced at the IAEA, including databases stored on the mainframe, LAN's and PC's. All IAEA Division Directors have been requested to register the existence of their databases with NESI. For the second edition database owners were requested to review the existing entries for their databases and answer four additional questions. The four additional questions concerned the type of database (e.g. Bibliographic, Text, Statistical etc.), the category of database (e.g. Administrative, Nuclear Data etc.), the available documentation and the type of media used for distribution. In the individual entries on the following pages the answers to the first two questions (type and category) is always listed, but the answers to the second two questions (documentation and media) is only listed when information has been made available

  17. HIV Structural Database

    Science.gov (United States)

    SRD 102 HIV Structural Database (Web, free access)   The HIV Protease Structural Database is an archive of experimentally determined 3-D structures of Human Immunodeficiency Virus 1 (HIV-1), Human Immunodeficiency Virus 2 (HIV-2) and Simian Immunodeficiency Virus (SIV) Proteases and their complexes with inhibitors or products of substrate cleavage.

  18. Balkan Vegetation Database

    NARCIS (Netherlands)

    Vassilev, Kiril; Pedashenko, Hristo; Alexandrova, Alexandra; Tashev, Alexandar; Ganeva, Anna; Gavrilova, Anna; Gradevska, Asya; Assenov, Assen; Vitkova, Antonina; Grigorov, Borislav; Gussev, Chavdar; Filipova, Eva; Aneva, Ina; Knollová, Ilona; Nikolov, Ivaylo; Georgiev, Georgi; Gogushev, Georgi; Tinchev, Georgi; Pachedjieva, Kalina; Koev, Koycho; Lyubenova, Mariyana; Dimitrov, Marius; Apostolova-Stoyanova, Nadezhda; Velev, Nikolay; Zhelev, Petar; Glogov, Plamen; Natcheva, Rayna; Tzonev, Rossen; Boch, Steffen; Hennekens, Stephan M.; Georgiev, Stoyan; Stoyanov, Stoyan; Karakiev, Todor; Kalníková, Veronika; Shivarov, Veselin; Russakova, Veska; Vulchev, Vladimir

    2016-01-01

    The Balkan Vegetation Database (BVD; GIVD ID: EU-00-019; http://www.givd.info/ID/EU-00- 019) is a regional database that consists of phytosociological relevés from different vegetation types from six countries on the Balkan Peninsula (Albania, Bosnia and Herzegovina, Bulgaria, Kosovo, Montenegro

  19. World Database of Happiness

    NARCIS (Netherlands)

    R. Veenhoven (Ruut)

    1995-01-01

    textabstractABSTRACT The World Database of Happiness is an ongoing register of research on subjective appreciation of life. Its purpose is to make the wealth of scattered findings accessible, and to create a basis for further meta-analytic studies. The database involves four sections:
    1.

  20. Dictionary as Database.

    Science.gov (United States)

    Painter, Derrick

    1996-01-01

    Discussion of dictionaries as databases focuses on the digitizing of The Oxford English dictionary (OED) and the use of Standard Generalized Mark-Up Language (SGML). Topics include the creation of a consortium to digitize the OED, document structure, relational databases, text forms, sequence, and discourse. (LRW)