Relevant bibliographies by topics / Data capture

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data capture'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Data capture"

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Srikanth I Chandan, O. "Advancing Clinical Data Capture: Embracing Electronic Data Capture (EDC) for Enhanced Efficiency and Quality." International Journal of Science and Research (IJSR) 12, no. 7 (July 5, 2023): 1261–64. http://dx.doi.org/10.21275/sr23717190711.

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Yong-Qiong Zhu, Yong-Qiong Zhu, Ye-Ming Cai Yong-Qiong Zhu, and Fan Zhang Ye-Ming Cai. "Motion Capture Data Denoising Based on LSTNet Autoencoder." 網際網路技術學刊 23, no. 1 (January 2022): 011–20. http://dx.doi.org/10.53106/160792642022012301002.

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<p>This paper proposes a novel deep learning-based optical motion capture denoising model encoder-LSTNet- decoder (ELD). ELD uses an autoencoder for manifold learning and decoder to remove jitter noise and missing noise effectively. It uses recurrent units in LSTNet to effectively obtain the spatial-temporal information of motion sequences, especially the periodic long-term and short-term features. In the denoising procedure, the kinetical characteristics of the motion are also considered so that the reconstructed deviation is smaller and can more accurately reflect the real action. We simulated ELD with the CMU database and compared it with the art-of-state methods. The experiment shows that ELD is a very effective denoising technique with lower reconstruction error, stronger robustness, and shorter running time.</p> <p>&nbsp;</p>
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Macdonald, A. J. D., and A. Simpson. "Field data capture." Psychiatric Bulletin 14, no. 5 (May 1990): 292–94. http://dx.doi.org/10.1192/pb.14.5.292.

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The process of psychiatric research, as distinct from its content, has been the subject of little comment. Central to present-day techniques are the use of questionnaires and more or less structured interviews. Pre-coded data are preferred, and even if there are few cases in any one study, the quantity of data collected for each usually compensates for this and justifies computer analysis, using statistical packages such as SPSS∗. The days of punched cards have passed (only in the last eight years in one centre of excellence), so at least one of the error-prone steps (transfer of data from paper schedules by card-puncher) has been abolished, but the major chore is still this process, albeit direct to magnetic media (floppy or hard disk).
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Bergstrom, Bradley J. "An analysis of multiple captures in Permoyscus with a critique on methodology." Canadian Journal of Zoology 64, no. 7 (July 1, 1986): 1407–11. http://dx.doi.org/10.1139/z86-209.

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Multiple captures obtained in Sherman traps are reported for Peromyscus maniculatus (66 intraspecific, 6 interspecific) and P. difficilis (12 intraspecific, 4 interspecific) in Colorado. Multiple capture frequency in P. maniculatus. (3.53%) was higher than in P. difficilis (1.94%), which probably resulted from the greater weights of P. difficilis. Only one case of injury or death was noted in 84 multiple captures. Multiple captures occurred in traps in which the treadles were significantly less sensitive to tripping than traps that captured single mice, which suggested that pairs of mice did not enter the traps simultaneoulsy. Adult mice were disproportionatley sampled in single captures because of the insensitivity of the tripping mechanism. For the same reason, immature mice were disproportionately sampled in multiple captures. These trap-related biases can create spurious age and sex associations within multiple captures. Trap bias should be tested explicitly before attempting to analyze multiple-capture data from single-capture traps. A "socially null" model of random encounter of traps by captured pairs fits many of the data presented here and is suggested as the appropriate null hypothesis for these analyses. If live-trapping data must be used to address questions of social behavior, the use of actual multiple-capture traps, preferably to study long-term associations between individuals, is suggested.
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Goel, Alexander K., Walter Scott Campbell, and Richard Moldwin. "Structured Data Capture for Oncology." JCO Clinical Cancer Informatics, no. 5 (February 2021): 194–201. http://dx.doi.org/10.1200/cci.20.00103.

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Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC’s primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data’s lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic—SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document.
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Kumar Alay, Prashanth. "Delivering a Clinical Trial Study Build in An Electronic Data Capture System for Data Collection." International Journal of Health Sciences and Research 13, no. 3 (March 14, 2023): 229–33. http://dx.doi.org/10.52403/ijhsr.20230324.

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All aspects of health, disease, and healthcare, encompass under Health Sciences. It indeed is a large group of disciplines, which through the application of technology, strives to deliver the best health care to humans. Subject data is generated in humongous amounts and data collection is deemed of utmost importance. As focus on patient’s experience continues to grow, virtual models for data collection and decentralized components have gained momentum. Electronic Data Capture (EDC) systems help capture clinical data and collect it from any source and harmonize it in a single place. Clinical data collected and captured, provides valuable clinical insights and a data capture system can be utilized for several study designs across various customers. Key words: [Electronic Data Capture (EDC), Case Report Form (CRF), User Acceptance Testing (UAT), a Clinical Database Management System (CDMS)]
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Attenni, Martina, Marika Griffo, Carlo Inglese, Alfonso Ippolito, Eric Lo, and Dominique Rissolo. "Flexibility of Dense 3D Data Capture." Studies in Digital Heritage 5, no. 1 (June 30, 2021): 62–74. http://dx.doi.org/10.14434/sdh.v5i1.31442.

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The knowledge and study of built heritage is now deeply connected to methodologies associated with the capture of surface details via the production of point-data. These methodologies enable researchers to gather a wider range of information, which is increasingly more connected to technological advances. Such approaches influence the management of data, and these data are often redundant due to the ways in which they are captured. Massive data capture does not include preliminary selection based on metric, geometric, and material features of the object. A multi-scalar approach, in which the criteria for data capture depends on the goals of the survey, is needed to optimize the relationship between information and the scale of the models to be built. This case study involving a selection of fountains in Rome aims to apply these principles to urban contexts defined by a strong spatial connection between architectural and sculptural elements. Survey can express this distinctiveness through complex, dynamic, and effective digital models.
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Hyde, Andrew William. "The Changing Face of Electronic Data Capture: From Remote Data Entry to Direct Data Capture." Drug Information Journal 32, no. 4 (October 1998): 1089–92. http://dx.doi.org/10.1177/009286159803200429.

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Helms, Ronald W. "Data Quality Issues in Electronic Data Capture." Drug Information Journal 35, no. 3 (July 2001): 827–37. http://dx.doi.org/10.1177/009286150103500320.

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Walther, Brigitte, Safayet Hossin, John Townend, Neil Abernethy, David Parker, and David Jeffries. "Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data." PLoS ONE 6, no. 9 (September 23, 2011): e25348. http://dx.doi.org/10.1371/journal.pone.0025348.

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Dissertations / Theses on the topic "Data capture"

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Connell, Edward B., William P. Barnes, and William H. Stallings. "The Generic Data Capture Facility." International Foundation for Telemetering, 1987. http://hdl.handle.net/10150/615290.

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International Telemetering Conference Proceedings / October 26-29, 1987 / Town and Country Hotel, San Diego, California
The growing complexity of space science missions is causing a dramatic increase in the data rates and volumes from spaced-based experiments, and the ground operations functions associated with handling data from these missions are growing in complexity consistent with this increase. A key requirement on the systems that provide data handling support is to control operations costs carefully while providing high-quality data capture functions. One approach to meeting this particular objective that has been taken at the Goddard Space Flight Center has been to initiate the development of a Generic Data Capture Facility (GDCF) that can provide data capture support for a variety of different types of spacecraft. The GDCF is emerging through a blend of new system development and evolution of existing systems, and when complete, it will have the capability to support the two major data formatting schemes (packet and Time-Division Multiplexed (TDM)). The specific implementations are designed to support the Gamma Ray Observatory and the Upper Atmosphere Research Satellite, but the GDCF will provide the baseline system to support various new missions as they emerge.
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Miller, Iain. "Finding associations in motion capture data." Thesis, University of the West of Scotland, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.729427.

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Turner, Elizabeth L. "Marginal modelling of capture-recapture data." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103302.

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The central theme of this dissertation is the development of a new approach to conceptualize and quantify dependence structures of capture-recapture data for closed populations, with specific emphasis on epidemiological applications. We introduce a measure of source dependence: the Coefficient of Incremental Dependence (CID). Properties of this and the related Coefficient of Source Dependence (CSD) of Vandal, Walker, and Pearson (2005) are presented, in particular their relationships to the conditional independence structures that can be modelled by hierarchical joint log-linear models (HJLLM). From these measures, we develop a new class of marginal log-linear models (MLLM), which we compare and contrast to HJLLMs.
We demonstrate that MLLMs serve to extend the universe of dependence structures of capture-recapture data that can be modelled and easily interpreted. Furthermore, the CIDs and CSDs enable us to meaningfully interpret the parameters of joint log-linear models previously excluded from the analysis of capture-recapture data for reasons of non-interpretability of model parameters.
In order to explore the challenges and features of MLLMs, we show how to produce inference from them under both a maximum likelihood and a Bayesian paradigm. The proposed modelling approach performs well and provides new insight into the fundamental nature of epidemiological capture-recapture data.
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Mayo, Timothy Robert. "Intelligent systems for cartographic data capture." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357566.

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Shi, Jiangpeng. "Wearable personal data information capture system." ScholarWorks@UNO, 2004. http://louisdl.louislibraries.org/u?/NOD,172.

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Thesis (M.S.)--University of New Orleans, 2004.
Title from electronic submission form. "A thesis ... in partial fulfillment of the requirements for the degree of Master of Science in the Department of Computer Science."--Thesis t.p. Vita. Includes bibliographical references.
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Larsson, Albin. "MC.d.o.t : Motion capture data och dess tillgänglighet." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9622.

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Hårdvara kan bli gammal, program kan sluta utvecklas, filer som skapats från sådan hårdvara respektive mjukvara kan bli oanvändbara med tiden. Samt att hålla ordning på många individuella filer kan i längden bli jobbigt för användare. Med en databasorienterad lagrinsgslösning kan olika API:er användas för att göra data kompatibel med flera olika verktyg och program, samt att det kan användas för att skapa en centraliserad lösning för att enkelt hålla ordning på information. Bland databaser finns det två primära grupperingar: SQL och NoSQL. Detta arbete ämnar undersöka vilken typ som passar för att hantera motion capture data. Tester har utförts på SQLs MySQL och NoSQLs Neo4j. Neo4j som är specialiserad för att hantera data som motion capture data. Resultatet från testningarna är förvånande nog att MySQL hanterar motion capture data bättre än Neo4j. Ytterligare arbeten för att undersöka fler varianter av databaser för en mer komplett bild föreslås.
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Rogers, Bennett Lee. "Query-by-example for motion capture data." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42255.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 57-58).
Motion capture datasets are employed widely in animation research and industry, however there currently exists no efficient way to index and search this data for diversified use. Motion clips are generally searched by filename or keywords, neither of which incorporates knowledge of actions in the clip aside from those listed in the descriptions. We present a method for indexing and searching a large database of motion capture clips that allows for fast insertion and query-by-example. Over time, more motions can be added to the index, incrementally increasing its value. The result is a tool that reduces the amount of time spent gathering new data for motion applications, and increases the utility of existing motion clips.
by Bennett Lee Rogers.
S.M.
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Wang, Zhao. "Motion capture data processing, retrieval and recognition." Thesis, Bournemouth University, 2018. http://eprints.bournemouth.ac.uk/31038/.

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Character animation plays an essential role in the area of featured film and computer games. Manually creating character animation by animators is both tedious and inefficient, where motion capture techniques (MoCap) have been developed and become the most popular method for creating realistic character animation products. Commercial MoCap systems are expensive and the capturing process itself usually requires an indoor studio environment. Procedural animation creation is often lacking extensive user control during the generation progress. Therefore, efficiently and effectively reusing MoCap data can brings significant benefits, which has motivated wider research in terms of machine learning based MoCap data processing. A typical work flow of MoCap data reusing can be divided into 3 stages: data capture, data management and data reusing. There are still many challenges at each stage. For instance, the data capture and management often suffer from data quality problems. The efficient and effective retrieval method is also demanding due to the large amount of data being used. In addition, classification and understanding of actions are the fundamental basis of data reusing. This thesis proposes to use machine learning on MoCap data for reusing purposes, where a frame work of motion capture data processing is designed. The modular design of this framework enables motion data refinement, retrieval and recognition. The first part of this thesis introduces various methods used in existing motion capture processing approaches in literature and a brief introduction of relevant machine learning methods used in this framework. In general, the frameworks related to refinement, retrieval, recognition are discussed. A motion refinement algorithm based on dictionary learning will then be presented, where kinematical structural and temporal information are exploited. The designed optimization method and data preprocessing technique can ensure a smooth property for the recovered result. After that, a motion refinement algorithm based on matrix completion is presented, where the low-rank property and spatio-temporal information is exploited. Such model does not require preparing data for training. The designed optimization method outperforms existing approaches in regard to both effectiveness and efficiency. A motion retrieval method based on multi-view feature selection is also proposed, where the intrinsic relations between visual words in each motion feature subspace are discovered as a means of improving the retrieval performance. A provisional trace-ratio objective function and an iterative optimization method are also included. A non-negative matrix factorization based motion data clustering method is proposed for recognition purposes, which aims to deal with large scale unsupervised/semi-supervised problems. In addition, deep learning models are used for motion data recognition, e.g. 2D gait recognition and 3D MoCap recognition. To sum up, the research on motion data refinement, retrieval and recognition are presented in this thesis with an aim to tackle the major challenges in motion reusing. The proposed motion refinement methods aim to provide high quality clean motion data for downstream applications. The designed multi-view feature selection algorithm aims to improve the motion retrieval performance. The proposed motion recognition methods are equally essential for motion understanding. A collection of publications by the author of this thesis are noted in publications section.
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Segelstad, Johan. "Layering animation principles on motion capture data : Surpass the limitations of motion capture." Thesis, Luleå tekniska universitet, Institutionen för konst, kommunikation och lärande, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74636.

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This thesis deals with the use of Disney's twelve animation principles in relation to Motion Capture. The purpose of the work was to investigate whether animation principles can be applied to finished motion capture animations to surpass the limitations of motion capture  by using animation layers, where each added layer is a new principle. To investigate this, motion capture data was retrieved with various movements from Mixamo, which was then imported into Maya where various animation principles were applied with the help of Maya animation layers. The result of this research will answer the following… Is it possible to surpass the limitations of motion capture by layering disney's animation principles on motion captured animations in Maya with the use of animation layers?
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De, Wet Francois Johan. "Data capture of geometric data for local authorities' geographic information systems." Master's thesis, University of Cape Town, 1995. http://hdl.handle.net/11427/14953.

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Bibliography: leaves 64-65.
This thesis describes research and development work which led to algorithms, procedures and computer programs which facilitate the cost effective and accurate capture of geometric data. The geometric data for a Geographical Information System (GIS) at a local authority or municipality consist of a number of different data sets. These include inter alia: the cadastral information, zoning information, servitudes, building lines, the outlines of improvements and the reticulation networks and the house connection points of the engineering services. The initial capture of the geometric data appears to be deceptively simple and is often not given the required consideration. The initial data capture phase of GIS projects is usually a difficult and time consuming process. This is even more so in the case of GIS for local authorities. The reason for this difficulty is the large volume of data coupled with the high accuracies required for the cadastral base map and the engineering services. Input facilities of most commercial GIS software packages generally do not provide the most efficient means of data capture. This problem warrants the development of techniques and procedures specific to local authority GIS applications which ensure that data capture can be done effectively and efficiently. The major benefit of these procedures is that they can be implemented on personal computers with low random access memory capacity. This eliminates the need for investment in costly equipment at the initial stage of data capture in the development of a GIS. It allows the capture of data on low cost technology and the postponement of the purchase of an expensive system or workstation until the data capture phase has been completed. The lowest personnel skills required are copy typing in contrast to the traditional methods of using CAD operators who command higher salaries and require more expensive training. The system developed by the author is more productive, both in quality and volume of work produced, than the CAD approach. It also permits the delay of purchase and training on expensive GIS software and hardware, which may be obsolete by the time the graphic database is established.
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Books on the topic "Data capture"

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Ahmed, Nazeer. Data capture unit for vision systems. Salford: University of Salford, 1987.

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Alberta Energy and Utilities Board. Electronic capture of well test data. Calgary, Alberta: Alberta Energy and Utilities Board, 1999.

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Askwith, S. C. Data capture and analysis of astronomical images. Manchester: UMIST, 1993.

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Kathy, Findlay, and Hertfordshire County Council, eds. Environmental data capture and release: Green issues. [Hertford]: [s.n.], 1993.

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Herniter, Marc E. Schematic capture with PSpice. New York: Merrill, 1994.

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1946-, Oldknow A. J., Taylor Ron 1948-, and British Educational Communications and Technology Agency., eds. Data-capture and modelling in mathematics and science. Coventry: British Educational Communications & Technology Agency, 1998.

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Inside OrCAD capture for Windows. Boston: Newnes, 1998.

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Schematic capture with Multisim 7. Upper Saddle River, N.J: Pearson/Prentice Hall, 2005.

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Herniter, Marc E. Schematic capture with MicroSim PSpice. 3rd ed. Upper Saddle River, N.J: Prentice Hall, 1998.

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Schematic capture with MicroSim PSpice. 4th ed. Englewood Cliffs, N.J: Prentice Hall, 1996.

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Book chapters on the topic "Data capture"

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Cramer, Michael, Wolfgang Kresse, Jan Skaloud, Norbert Haala, Silvia Nittel, and Jan O. Wallgrün. "Data Capture." In Springer Handbook of Geographic Information, 119–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-72680-7_9.

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Günther, Oliver. "Data Capture." In Environmental Information Systems, 9–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03602-0_2.

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Weik, Martin H. "data capture." In Computer Science and Communications Dictionary, 341. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4205.

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Raina, Vineet, and Srinath Krishnamurthy. "Data Capture." In Building an Effective Data Science Practice, 163–72. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7419-4_13.

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Gupta, Saurabh, and Venkata Giri. "Capture Streaming Data with Change-Data-Capture." In Practical Enterprise Data Lake Insights, 87–123. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3522-5_3.

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Alley-Young, Gordon. "Keystroke Capture." In Encyclopedia of Big Data, 609–14. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-32010-6_125.

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Alley-Young, Gordon. "Keystroke Capture." In Encyclopedia of Big Data, 1–6. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-32001-4_125-1.

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Nahler, Gerhard. "data capture document." In Dictionary of Pharmaceutical Medicine, 45. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_337.

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Malmström, Lars, Andreas Quandt, and Ela Pustulka-Hunt. "Proteomics Data Capture." In Encyclopedia of Systems Biology, 1795–97. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1001.

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Savoye, Yann. "Reusing Performance Capture Data." In Cage-based Performance Capture, 53–92. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01538-5_3.

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Conference papers on the topic "Data capture"

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Snoddy, Dan, James Spyker, Mir Rupik, Mike Jory, and Kris Kobylinski. "Change data capture." In the 2009 Conference of the Center for Advanced Studies. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1723028.1723064.

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Wilson, S. J. "Data - to capture or not to capture?" In IET & IAM Asset Management Conference 2012. Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.1903.

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LYON, JOHN, GENE SMITH, and RICHARD CARPER. "Data capture and processing." In International Symposium on Space Information in the Space Station Era. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-2203.

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Manatt, D. R., F. L. Barnes, J. A. Becker, J. V. Candy, E. A. Henry, and M. J. Brinkman. "Pattern Recognition in Gamma‐Gamma Coincidence Data sets." In Capture gamma‐ray spectroscopy. American Institute of Physics, 1991. http://dx.doi.org/10.1063/1.41219.

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Daga, Enrico, Mathieu d'Aquin, and Enrico Motta. "Propagating Data Policies." In K-CAP 2017: Knowledge Capture Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3148011.3148022.

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Portugal, Ivens, Paulo Alencar, and Donald Cowan. "Computational Analysis to Capture Cluster Lifetime Dynamics." In 2021 IEEE International Conference on Big Data (Big Data). IEEE, 2021. http://dx.doi.org/10.1109/bigdata52589.2021.9671317.

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Wolf, A., S. Kahane, and Y. Birenbaum. "Systematics of 3.5 to 100 MeV 2H(γ,n) Data." In Capture gamma‐ray spectroscopy. American Institute of Physics, 1991. http://dx.doi.org/10.1063/1.41230.

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Robinson, S. J. "Extraction of Spins and Mixing Ratios from Directional Correlation Data." In Capture gamma‐ray spectroscopy. American Institute of Physics, 1991. http://dx.doi.org/10.1063/1.41251.

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Wood, Terri. "EDOS Data Capture for ALOS." In SpaceOps 2012. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-1295673.

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Gentile, Anna Lisa, Ziqi Zhang, Isabelle Augenstein, and Fabio Ciravegna. "Unsupervised wrapper induction using linked data." In K-CAP 2013: Knowledge Capture Conference. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2479832.2479845.

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Reports on the topic "Data capture"

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Pickett, Dayton S. Individual Enlisted Training Data Capture and Management. Fort Belvoir, VA: Defense Technical Information Center, January 1988. http://dx.doi.org/10.21236/ada206382.

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2

Gilbert, C., K. Parlee, and D. J. Scott. A Palm-based digital field-data capture system. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/212177.

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Orandi, Shahram, Craig Watson, John M. Libert, Gregory P. Fiumara, and John D. Grantham. Contactless Fingerprint Capture and Data Interchange Best Practice Recommendation. National Institute of Standards and Technology, March 2021. http://dx.doi.org/10.6028/nist.sp.500-334.

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Evans, J. M., T. Chang, T. H. Hong, R. Bostelman, and W. R. Bunch. Three dimensional data capture in indoor environments for autonomous navigation. Gaithersburg, MD: National Institute of Standards and Technology, 2002. http://dx.doi.org/10.6028/nist.ir.6912.

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Rebai, Adlane, Alex Strickland, Alexander Szewczak, Anurag Sharma, Bob Lenich, Dave Pazzani, Derrick Tapscott, et al. Implementing an ontology and digital data capture to improve biomanufacturing. BioPhorum, November 2023. http://dx.doi.org/10.46220/2023ts005.

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Evans, Tyler, Eric Hileman, Melanie Boudreau, Bronson Strickland, and Raymond Iglay. Capture history data from hair snare sampling of wild pigs in Mississippi. Mississippi State University, 2024. http://dx.doi.org/10.54718/kxka1060.

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Capture histories of wild pigs (Sus scrofa) identified using nuclear DNA markers from hair snare samples activated on the Sam D. Hamilton Noxubee National Wildlife Refuge in Mississippi between 2021 and 2022. Hair snares were active for 8 weeks (occassions) with non-grain attractants placed at the center of each snare. Dat includes unique pig identifiers (Pig_ID), capture histories (Capture_Occassion), and associated capture year (Group).
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Pritychenko, B., and B. Pritychenko. Nuclear Data Resources for Capture gamma-Ray Spectroscopy and Related Topics. Office of Scientific and Technical Information (OSTI), August 2011. http://dx.doi.org/10.2172/1029252.

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8

Margenau, Eric, and Lenza Paul. A 23-year summary of a Monitoring Avian Productivity and Survivorship (MAPS) bird banding site in New River Gorge National River, West Virginia. National Park Service, August 2021. http://dx.doi.org/10.36967/nrr-2287051.

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Long-term bird banding data were collected from 1996–2019 (except in 2008) to assess the New River riparian zone avian community in one location in New River Gorge National River (NERI). The NERI banding station has banded over 4,500 individuals over 10,700 net hours in the twenty-three years it has been in operation and has captured 80 different species. Total captures, capture rate, and total species have been declining annually over the study period. Species associated with early-successional/shrubland habitat also declined over the study period, which is consistent with regional trends during the same time frame. Species richness of habitat guilds did not change over the study period within specific major habitat types. Capture metrics of Louisiana Waterthrush, an obligate riparian species, did increase over the study period. Continued banding will further provide information to assist in local management and contribute to regional data.
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Shimamura, K., S. P. Williams, and G. Buller. GanFeld user guide: a map-based field data capture system for geologists. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2008. http://dx.doi.org/10.4095/226214.

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Clark, J. K., T. R. Carter, F. R. Brunton, C. E. Logan, M. Somers, L. Sutherland, and K. Yeung. Improving the 3-D geological data infrastructure of southern Ontario: data capture, compilation, enhancement and QA/QC. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2020. http://dx.doi.org/10.4095/321081.

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