Academic literature on the topic 'Alignement de data elements'
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Journal articles on the topic "Alignement de data elements"
Hamzić, Adis, and Dina Kamber Hamzić. "Dam Movement Modeling by Using Multiple Linear Regression and Arima Models." Geodetski glasnik, no. 51 (December 31, 2020): 49–64. http://dx.doi.org/10.58817/2233-1786.2020.54.51.49.
Full textNahm, Meredith, Anita Walden, Brian McCourt, Karen Pieper, Emily Honeycutt, Carol D. Hamilton, Robert A. Harrington, et al. "Standardising clinical data elements." International Journal of Functional Informatics and Personalised Medicine 3, no. 4 (2010): 314. http://dx.doi.org/10.1504/ijfipm.2010.040213.
Full textColeman, David E. "Elements of Graphing Data." Technometrics 29, no. 1 (February 1987): 116–18. http://dx.doi.org/10.1080/00401706.1987.10488193.
Full textVillere, Sarah. "Common Data Elements Repository." Medical Reference Services Quarterly 43, no. 2 (April 2, 2024): 182–90. http://dx.doi.org/10.1080/02763869.2024.2323896.
Full textPipere, Anita, and Ilona Mičule. "Mathematical Identity for a Sustainable Future: An Interpretative Phenomenological Analysis." Journal of Teacher Education for Sustainability 16, no. 1 (June 1, 2014): 5–31. http://dx.doi.org/10.2478/jtes-2014-0001.
Full textM., D. W., and William S. Cleveland. "The Elements of Graphing Data." American Journal of Psychology 99, no. 3 (1986): 443. http://dx.doi.org/10.2307/1422498.
Full textSrivastava, Rajendra, and William S. Cleveland. "The Elements of Graphing Data." Journal of Marketing Research 24, no. 4 (November 1987): 461. http://dx.doi.org/10.2307/3151402.
Full textSchnell, Gary D., and William S. Cleveland. "The Elements of Graphing Data." Systematic Zoology 34, no. 4 (December 1985): 471. http://dx.doi.org/10.2307/2413211.
Full textWaterhouse, J. M. "The Elements of Graphing Data." Journal of Arid Environments 12, no. 1 (January 1987): 83. http://dx.doi.org/10.1016/s0140-1963(18)31200-x.
Full textZiegel, Eric R., and William S. Cleveland. "The Elements of Graphing Data." Technometrics 39, no. 2 (May 1997): 237. http://dx.doi.org/10.2307/1270929.
Full textDissertations / Theses on the topic "Alignement de data elements"
Griffier, Romain. "Intégration et utilisation secondaire des données de santé hospitalières hétérogènes : des usages locaux à l'analyse fédérée." Electronic Thesis or Diss., Bordeaux, 2024. http://www.theses.fr/2024BORD0479.
Full textHealthcare data can be used for purposes other than those for which it was initially collected: this is the secondary use of health data. In the hospital context, to overcome the obstacles to secondary use of healthcaree data (data and organizational barriers), a classic strategy is to set up Clinical Data Warehouses (CDWs). This thesis describes three contributions to the Bordeaux University Hospital’s CDW. Firstly, an instance-based, privacy-preserving, method for mapping numerical biology data elements is presented, with an F-measure of 0,850, making it possible to reduce the semantic heterogeneity of data. Next, an adaptation of the i2b2 clinical data integration model is proposed to enable CDW data persistence in a NoSQL database, Elasticsearch. This implementation has been evaluated on the Bordeaux University Hospital’s CDW, showing improved performance in terms of storage and query time, compared with a relational database. Finally, the Bordeaux University Hospital’s CDW environment is presented, with the description of a first CDW dedicated to local uses that can be used autonomously by end users (i2b2), and a second CDW dedicated to federated networks (OMOP) enabling participation in the DARWIN-EU federated network
Xiao, Katharine (Katharine J. ). "Towards automatically linking data elements." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113450.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 91-92).
When presented with a new dataset, human data scientists explore it in order to identify salient properties of the data elements, identify relationships between entities, and write processing software that makes use of those relationships accordingly. While there has been progress made on automatically processing the data to generate features or models, most automation systems rely on receiving a data model that has all the meta information about the data, including salient properties and relationships. In this thesis, we present a first version of our system, called ADEL-Automatic Data Elements Linking. Given a collection of files, this system generates a relational data schema and identifies other salient properties. It detects the type of each data field, which describes not only the programmatic data type but also the context in which the data originated, through a method called Type Detection. For each file, it identifies the field that uniquely describes each row in it, also known as a Primary Key. Then, it discovers relationships between different data entities with Relationship Discovery, and discovers any implicit constraints in the data through Hard Constraint Discovery. We posit two out of these four problems as learning problems. To evaluate our algorithms, we compare the results of each to a set of manual annotations. For Type Detection, we saw a max error of 7%, with an average error of 2.2% across all datasets. For Primary Key Detection, we classified all existing primary keys correctly, and had one false positive across five datasets. For Relationship Discovery, we saw an average error of 5.6%. (Our results are limited by the small number of manual annotations we currently possess.) We then feed the output of our system into existing semi-automated data science software systems - the Deep Feature Synthesis (DFS) algorithm, which generates features for predictive models, and the Synthetic Data Vault (SDV), which generates a hierarchical graphical model. When ADEL's data annotations are fed into DFS, it produces similar or higher predictive accuracy in 3/4 problems, and when they are provided to SDV, it is able to generate synthetic data with no constraint violations.
by Katharine Xiao.
M. Eng.
Fan, Zhengjie. "Concise Pattern Learning for RDF Data Sets Interlinking." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM013/document.
Full textThere are many data sets being published on the web with Semantic Web technology. The data sets usually contain analogous data which represent the similar resources in the world. If these data sets are linked together by correctly identifying the similar instances, users can conveniently query data through a uniform interface, as if they are connecting a single database. However, finding correct links is very challenging because web data sources usually have heterogeneous ontologies maintained by different organizations. Many existing solutions have been proposed for this problem. (1) One straight-forward idea is to compare the attribute values of instances for identifying links, yet it is impossible to compare all possible pairs of attribute values. (2) Another common strategy is to compare instances with correspondences found by instance-based ontology matching, which can generate attribute correspondences based on overlapping ranges between two attributes, while it is easy to cause incomparable attribute correspondences or undiscovered comparable attribute correspondences. (3) Many existing solutions leverage Genetic Programming to construct interlinking patterns for comparing instances, however the running times of the interlinking methods are usually long. In this thesis, an interlinking method is proposed to interlink instances for different data sets, based on both statistical learning and symbolic learning. On the one hand, the method discovers potential comparable attribute correspondences of each class correspondence via a K-medoids clustering algorithm with instance value statistics. We adopt K-medoids because of its high working efficiency and high tolerance on irregular data and even incorrect data. The K-medoids classifies attributes of each class into several groups according to their statistical value features. Groups from different classes are mapped when they have similar statistical value features, to determine potential comparable attribute correspondences. The clustering procedure effectively narrows the range of candidate attribute correspondences. On the other hand, our solution also leverages a symbolic learning method, called Version Space. Version Space is an iterative learning model that searches for the interlinking pattern from two directions. Our design can solve the interlinking task that does not have a single compatible conjunctive interlinking pattern that covers all assessed correct links with a concise format. The interlinking solution is evaluated with large-scale real-world data from IM@OAEI and CKAN. Experiments confirm that the solution with only 1% of sample links already reaches a high accuracy (up to 0.94-0.99 on F-measure). The F-measure quickly converges improving on other state-of-the-art approaches, by nearly 10 percent of their F-measure values
Cherif, Mohamed Abderrazak. "Alignement et fusion de cartes géospatiales multimodales hétérogènes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5002.
Full textThe surge in data across diverse fields presents an essential need for advanced techniques to merge and interpret this information. With a special emphasis on compiling geospatial data, this integration is crucial for unlocking new insights from geographic data, enhancing our ability to map and analyze trends that span across different locations and environments with more authenticity and reliability. Existing techniques have made progress in addressing data fusion; however, challenges persist in fusing and harmonizing data from different sources, scales, and modalities.This research presents a comprehensive investigation into the challenges and solutions in vector map alignment and fusion, focusing on developing methods that enhance the precision and usability of geospatial data. We explored and developed three distinct methodologies for polygonal vector map alignment: ProximityAlign, which excels in precision within urban layouts but faces computational challenges; the Optical Flow Deep Learning-Based Alignment, noted for its efficiency and adaptability; and the Epipolar Geometry-Based Alignment, effective in data-rich contexts but sensitive to data quality. Additionally, our study delved into linear feature map alignment, emphasizing the importance of precise alignment and feature attribute transfer, pointing towards the development of richer, more informative geospatial databases by adapting the ProximityAlign approach for linear features like fault traces and road networks. The fusion aspect of our research introduced a sophisticated pipeline to merge polygonal geometries relying on space partitioning, non-convex optimization of graph data structure, and geometrical operations to produce a reliable fused map that harmonizes input vector maps, maintaining their geometric and topological integrity.In practice, the developed framework has the potential to improve the quality and usability of integrated geospatial data, benefiting various applications such as urban planning, environmental monitoring, and disaster management. This study not only advances theoretical understanding in the field but also provides a solid foundation for practical applications in managing and interpreting large-scale geospatial datasets
Westermark, Vicky. "EVALUATING VIEWS FOR PRODUCING DERIVED DATA ELEMENTS ON TIME SERIES DATA." Thesis, Umeå universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-175898.
Full textSoheily-Khah, Saeid. "Generalized k-means-based clustering for temporal data under time warp." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM064/document.
Full textTemporal alignment of multiple time series is an important unresolved problem in many scientific disciplines. Major challenges for an accurate temporal alignment include determining and modeling the common and differential characteristics of classes of time series. This thesis is motivated by recent works in extending Dynamic time warping for aligning multiple time series from several applications including speech recognition, curve matching, micro-array data analysis, temporal segmentation or human motion. However these DTW-based works suffer of several limitations: 1) They address the problem of aligning two time series regardless of the remaining time series, 2) They involve uniformly the features of the multiple time series, 3) The time series are aligned globally by including the whole observations. The aim of this thesis is to explore a generalized dynamic time warping for time series clustering. This work includes first the problem of prototype extraction, then the alignment of multiple and multidimensional time series
RAPUR, NIHARIKA. "TREATMENT OF DATA WITH MISSING ELEMENTS IN PROCESS MODELLING." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1060192778.
Full textBlock, Lorraine Joy. "Mapping nursing wound care data elements to SNOMED-CT." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/60290.
Full textApplied Science, Faculty of
Nursing, School of
Graduate
Speed, Erek R. "Detecting high level story elements from low level data." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/77019.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (p. 57-58).
The problem addressed here is yet another artificial intelligence problem that is easily solved by young children yet challenges even sophisticated computer programs. This thesis's canonical example is a scene featuring two entities drinking. In one scene, a cat drinks from a faucet. In the other, a human drinks from a glass. Even young humans can identify that the two images are similar in that they both involve drinking. However, low-level analysis of the scene will find many more differences than similarities in the case cited above. In my research examines ways to detect high-level story elements such as drinking from low-level data such as that which might be produced from analyzing pictures and videos directly. I present a system that accepts as input a collection of high-level events represented in transition space. I analyze, then select the affinity propagation clustering algorithm to group the events using only their low-level representations. To this end, I present a novel algorithm for determining how similar any two points in transition space are. Due to the lack of vision systems capable of providing a varied dataset, I create a system which translates English language descriptions of high-level events and produces a specially formatted transition space file. To support my hypotheses, I presents the results of two experiments using the system described in this thesis. The first experiment uses English language files and the second uses data produced from a set of experimental videos. Using the English language files the system was able to detect groups corresponding to flying and walking among others out of a total set of 16 events.
by Erek R. Speed.
M.Eng.
Pelan, John Christopher. "The calculation of electron excitation data for iron group elements." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388173.
Full textBooks on the topic "Alignement de data elements"
Holgu�n-Vera, s. Jos�, Jeffrey Wojtowicz, Carlos Gonz�lez-Calder�n, Michael Lawrence, Jonathan Skolnik, Michael Brooks, Shanshan Zhang, Anne Strauss-Wieder, and L�ri Tavasszy. Freight Data Cost Elements. Washington, D.C.: Transportation Research Board, 2013. http://dx.doi.org/10.17226/21939.
Full textNational Information Standards Organization (U.S.). Interlibrary loan data elements. Bethesda, Md., U.S.A: NISO Press, 1995.
Find full textSystem, Central Ohio Trauma. Data elements instruction manual. 3rd ed. Columbus, Ohio: Central Ohio Trauma System, 1999.
Find full textInstitute, American National Standards, ed. Interlibrary loan data elements: American national standard for interlibrary loan data elements. New Brunswick, N.J., U.S.A: Transaction Publishers, 1990.
Find full textPrice, Wilson T. Elements of data processing mathematics. 3rd ed. New York: Holt, Rinehart, and Winston, 1987.
Find full textCleveland, William S. The elements of graphing data. Monterey, Calif: Wadsworth, 1985.
Find full textCleveland, William S. The elements of graphing data. Monterey, Calif: Wadsworth Advanced Books and Software, 1985.
Find full textCleveland, William S. The elements of graphing data. Murray Hill, N.J: AT&T Bell Laboratories, 1994.
Find full textCleveland, William S. The elements of graphic data. Murray Hill, N.J: AT & T Bell, 1994.
Find full textC, Guptill Stephen, Morrison Joel L, and International Cartographic Association, eds. Elements of spatial data quality. Oxford, U.K: Elsevier Science, 1995.
Find full textBook chapters on the topic "Alignement de data elements"
Walters, R. B. "Data Transmission Elements." In Hydraulic and Electric-Hydraulic Control Systems, 25–29. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9427-1_6.
Full textWalters, R. B. "Data Transmission Elements." In Hydraulic and Electro-Hydraulic Control Systems, 25–29. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3840-6_6.
Full textMadelung, Otfried. "Group III elements." In Semiconductors: Data Handbook, 397–403. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18865-7_12.
Full textMadelung, Otfried. "Group V elements." In Semiconductors: Data Handbook, 404–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18865-7_13.
Full textMadelung, Otfried. "Group VI elements." In Semiconductors: Data Handbook, 419–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18865-7_14.
Full textPlaue, Matthias. "Elements of data organization." In Data Science, 11–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-67882-4_1.
Full textBuchanan, William J. "Networking Elements." In Advanced Data Communications and Networks, 423–44. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4419-8670-2_27.
Full textMartienssen, Werner. "The Elements." In Springer Handbook of Materials Data, 41–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69743-7_4.
Full textBuchanan, W. "Networking Elements." In Advanced Data Communications and Networks, 423–44. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003420415-27.
Full textBanerjee, Sreeparna. "Multimedia Data Compression." In Elements of Multimedia, 107–31. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2019.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429433207-7.
Full textConference papers on the topic "Alignement de data elements"
Chopra, Darshan, Shashank Shekhar, Ancy Christopher, Vinay M, and Kavitha S. "Decoding Big Data: The Essential Elements Shaping Business Intelligence." In 2024 8th International Conference on Computational System and Information Technology for Sustainable Solutions (CSITSS), 1–6. IEEE, 2024. https://doi.org/10.1109/csitss64042.2024.10816944.
Full textRabenorosoa, K., C. Cle´vy, S. Bargiel, J. P. Mascaro, P. Lutz, and C. Gorecki. "Modular and Reconfigurable 3D Micro-Optical Benches: Concept, Validation, and Characterization." In ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50160.
Full textUnverdi, N. Ozlem, and N. Aydin Unverdi. "Data analysis in optical circuit elements." In 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU). IEEE, 2010. http://dx.doi.org/10.1109/siu.2010.5651419.
Full textKalus, Christian K., and Michal Simecek. "Elements of hierarchical mask data preparation." In 18th European Mask Conference on Mask Technology for Integrated Circuits and Micro-Components. SPIE, 2002. http://dx.doi.org/10.1117/12.479334.
Full textKorsmeyer, David, Joan Walton, Bruce Gilbaugh, and Dennis Koga. "DARWIN - Remote access data visualization elements." In Advanced Measurement and Ground Testing Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-2250.
Full textLiu, Xiteng. "Essential Data Elements: Extraction and Recovery." In 2017 IEEE 20th International Symposium on Real-Time Distributed Computing (ISORC). IEEE, 2017. http://dx.doi.org/10.1109/isorc.2017.12.
Full textCretu, P., and C. Steiner-Luckabauer. "Structural Elements Detection in Seismic Data." In 73rd EAGE Conference and Exhibition incorporating SPE EUROPEC 2011. Netherlands: EAGE Publications BV, 2011. http://dx.doi.org/10.3997/2214-4609.20149668.
Full textPopovici, Dana. "Context Elements for Transportation Services." In 2010 Eleventh International Conference on Mobile Data Management. IEEE, 2010. http://dx.doi.org/10.1109/mdm.2010.20.
Full textYamanaka, Yutaka, Ryuichi Katayama, Yuichi Komatsu, Seiji Ishikawa, M. Itoh, and Yuzo Ono. "Compact magneto-optical disk head integrated with chip elements." In Optical Data Storage, edited by James J. Burke, Thomas A. Shull, and Nobutake Imamura. SPIE, 1991. http://dx.doi.org/10.1117/12.45915.
Full textYamanaka, Y., R. Katayama, Y. Komatsu, S. Ishikawa, M. Itoh, and Y. Ono. "Compact Magneto-Optical Disk Head Integrated with Chip Elements." In Optical Data Storage. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/ods.1991.tuc4.
Full textReports on the topic "Alignement de data elements"
Kashima, S., and P. Aitken. Information Elements for Data Link Layer Traffic Measurement. Edited by A. Kobayashi. RFC Editor, May 2014. http://dx.doi.org/10.17487/rfc7133.
Full textSidorsky, Raymond C. Data Elements for Workload Analysis of Armored Vehicle Crews. Fort Belvoir, VA: Defense Technical Information Center, September 1990. http://dx.doi.org/10.21236/ada228422.
Full textDurling, P., and F. Marillier. Stratigraphy and structural elements of the Cumberland Basin from seismic reflection data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1996. http://dx.doi.org/10.4095/208198.
Full textPigni, Marco, Richard deBoer, and Paraskevi Dimitriou. International Nuclear Data Evaluation Network (INDEN) on the Evaluation of Light Elements. Office of Scientific and Technical Information (OSTI), June 2023. http://dx.doi.org/10.2172/1994989.
Full textFermi Research Alliance and Northern Illinois University. Design and Construction of Detector and Data Acquisition Elements for Proton Computed Tomography. Office of Scientific and Technical Information (OSTI), July 2015. http://dx.doi.org/10.2172/1333132.
Full textdeBoer, Richard J., and Paraskevi Dimitriou. International Nuclear Data Evaluation Network (INDEN) on the Evaluation of Light Elements (2). IAEA Nuclear Data Section, August 2019. http://dx.doi.org/10.61092/iaea.acf3-gjj4.
Full textdeBoer, Richard J., and Paraskevi Dimitriou. International Nuclear Data Evaluation Network (INDEN) Meeting on the Evaluation of Light Elements. IAEA Nuclear Data Section, November 2018. http://dx.doi.org/10.61092/iaea.0zgf-6yg6.
Full textBlessington, M. J., M. B. Werdon, S. S. Seitz, and K. M. Mulliken. Digital compilation of geochemical data for historical samples from occurrences of strategic and critical elements in Alaska: Part I - Rare-earth elements (REE). Alaska Division of Geological & Geophysical Surveys, December 2016. http://dx.doi.org/10.14509/29473.
Full textReioux, D. A., M. B. Werdon, S. S. Seitz, and K. M. Mulliken. Digital compilation of geochemical data for historical samples from occurrences of strategic and critical elements in Alaska: Part II - Platinum group elements (PGE). Alaska Division of Geological & Geophysical Surveys, December 2016. http://dx.doi.org/10.14509/29474.
Full textDurling, P., and F. Marillier. Structural elements of the Magdalen Basin, Gulf of St. Lawrence, from seismic reflection data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/134281.
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