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Relevant bibliographies by topics / Data extractions

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Academic literature on the topic 'Data extractions'

Author: Grafiati

Published: 25 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Data extractions"

1

Hamasha, Abed Al-Hadi, Mansour Ali Al Qudah, Anwar Barakat Bataineh, and Rima Ahmad Safadi. "Reasons for Third Molar Teeth Extraction in Jordanian Adults." Journal of Contemporary Dental Practice 7, no. 5 (2006): 88–95. http://dx.doi.org/10.5005/jcdp-7-5-88.

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Abstract Aims To assess reasons for third molar teeth extractions in a sample of Jordanian dental patients and to evaluate the association of extractions with other independent variables. Methods and Materials The study sample was comprised of dental patients in North Jordan who had third molar extractions. Data were collected from 36 dentists who were instructed to administer questionnaires to their adult patients undergoing third molar extractions and then to record the primary reason for those extractions. The data in this study was analyzed using a descriptive summary and chi square statistics. Results Dentists performed 810 extractions for 648 patients. The reasons for the extractions were: dental caries and its consequences about 42%, eruption problems 39%, periodontal diseases about 7%, and approximately 9% of extractions were a result of the dentist.s choice. The percentage of extractions due to dental caries significantly increased with increasing age. However, significant numbers of teeth were extracted due to eruption problems (51%-69%) in young adults. For 46+ year olds, 23% of extractions were caused by periodontal diseases. Extraction due to dental caries was distributed equally among the sexes. Persons with irregular tooth brushing and fewer dental visits had significantly more third molar teeth extracted due to caries and periodontal diseases compared to persons with regular tooth brushing and dental visits. Citation Hamasha AA, Al Qudah MA, Bataineh AB, Safadi RA. Reasons for Third Molar Teeth Extraction in Jordanian Adults. J Contemp Dent Pract 2006 November;(7)5:088-095.

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Brown, Ron H., and Irene Mueller-harvey. "Evaluation of the Novel Soxflo Technique for Rapid Extraction of Crude Fat in Foods and Animal Feeds." Journal of AOAC INTERNATIONAL 82, no. 6 (November 1, 1999): 1369–74. http://dx.doi.org/10.1093/jaoac/82.6.1369.

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Abstract The new Soxflo instrument was evaluated for the determination of crude fat in foods and animal feeds. Samples are packed into small columns and extracted with petroleum ether at room temperature. The Soxflo yielded accurate data from foods, ranging from 0.4 to 73.2% crude fat, compared with Soxhlet extractions and Certified Reference Materials, for which recoveries averaged 99.7 and 100.7%, respectively. Relative standard deviations (1.81 %) were approximately half those of Soxhlet extractions (3.68%). Regression analysis of the data suggested that there was no proportional bias. A small but acceptable constant bias was measured. Soxflo extractions are easy to perform and take approximately 1 h to complete. The main difference between the Soxflo and Soxhlet techniques lies in the extraction procedure. Estimated savings during extractions are in time (85% reduction), energy (95%), cooling water (100%), and solvents (50%). Soxflo extractions are, therefore, more environmentally friendly than Soxhlet extractions.

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Manya Suresh, Dhanraj Ganapathy, and Nivethigaa B. "Prevalence of full mouth extraction among patients visiting a dental college - A retrospective analysis." International Journal of Research in Pharmaceutical Sciences 11, SPL4 (December 25, 2020): 660–64. http://dx.doi.org/10.26452/ijrps.v11ispl4.4014.

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Extraction of teeth is one of the most common procedures carried out in dental clinics. This study was done to assess the prevalence of full mouth extraction among patients visiting a dental college. A review of the records of patients who had undergone tooth extraction in Saveetha Dental College between June 2019 to March 2020 was retrieved. Data was then analyzed for patients who had undergone full mouth extractions. Data was cross-tabulated based on gender. A total of 4539 patients had undergone extractions. Most of the patients were above the age of 40. There was a slightly higher predilection of males who had undergone extractions compared to females. 2.8% of the population had undergone full mouth extraction. Within the limits of the present study, it can be concluded that the prevalence of full mouth extraction cases in a dental college in Chennai was minimal, with a slightly higher predilection towards males.

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Pujara, Jay, Hui Miao, Lise Getoor, and William W. Cohen. "Using Semantics and Statistics to Turn Data into Knowledge." AI Magazine 36, no. 1 (March 25, 2015): 65–74. http://dx.doi.org/10.1609/aimag.v36i1.2568.

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Many information extraction and knowledge base construction systems are addressing the challenge of deriving knowledge from text. A key problem in constructing these knowledge bases from sources like the web is overcoming the erroneous and incomplete information found in millions of candidate extractions. To solve this problem, we turn to semantics — using ontological constraints between candidate facts to eliminate errors. In this article, we represent the desired knowledge base as a knowledge graph and introduce the problem of knowledge graph identification, collectively resolving the entities, labels, and relations present in the knowledge graph. Knowledge graph identification requires reasoning jointly over millions of extractions simultaneously, posing a scalability challenge to many approaches. We use probabilistic soft logic (PSL), a recently-introduced statistical relational learning framework, to implement an efficient solution to knowledge graph identification and present state-of-the-art results for knowledge graph construction while performing an order of magnitude faster than competing methods.

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Cahen, P. M., R. M. Frank, and J. C. Turlot. "A Survey of the Reasons for Dental Extractions in France." Journal of Dental Research 64, no. 8 (August 1985): 1087–93. http://dx.doi.org/10.1177/00220345850640081401.

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3516 French dentists, selected at random, were asked to record every tooth they extracted during January, 1984. They were also asked to give the reason for extraction in each case. These were assigned to eight groups: caries, periodontal diseases, eruption problems, prosthetics, trauma, orthodontics, occlusal problems, and other reasons. Data were received from 910 dentists (25.3%) relating to a total of 14,621 extractions. Overall, caries was the most frequent cause for extraction (49%), followed by periodontal diseases (32.4%) and orthodontics (8.4%). In the age group under 50, dental caries was the main reason for extraction. However, in the age group over 50, periodontal diseases became the principal reason for extraction. Orthodontic extractions were most prominent in the 6-12 and 13-20 age groups, with respective frequencies of 72.6% and 24.8% of all extractions. Eruption problems contributed most frequently in the 13-20 and 21-30 age groups, their respective percentages being 8.7% and 12.3%. Extractions resulting from trauma were most frequently noted in the under-6 age group (frequency of 8.8%). As far as the type of tooth was concerned, first and second molars taken together made up 29.6% of extractions These were followed by pre-molars, anterior teeth, and third molars at levels of 25.8%, 29.9%, and 14.7%, respectively. The teeth most frequently extracted because of caries were the molars (40.9%); because of periodontal disease, the anteriors (49.1%); and, for prosthetic reasons, again the anteriors (57.5%). Extractions from the various regions of France showed important variations. Percentage frequencies for caries and periodontal extractions were inversely linked.

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Brunello, Giulia, Marleen De Biagi, Giulia Crepaldi, Fernanda Izaura Rodrigues, and Stefano Sivolella. "An Observational Cohort Study on Delayed-Onset Infections after Mandibular Third-Molar Extractions." International Journal of Dentistry 2017 (2017): 1–5. http://dx.doi.org/10.1155/2017/1435348.

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Objectives. The purpose of the present study was to investigate the occurrence and clinical features of delayed-onset infections after mandibular third-molar extractions. Method and Materials. An observational cohort study was conducted on 179 patients undergoing mandibular third-molar extraction between January 2013 and December 2015, for a total of 217 extractions. Data were recorded at the time of extraction (T0), on suture removal seven days later (T1), and 30 days after the extraction, when patients were contacted and asked about their healing process (T2). The statistical analysis was performed with nonparametric tests. A p value lower than 0.05 was considered statistically significant. Results. Eight delayed-onset infections were recorded, amounting to 3.7% of all extractions. The median time elapsing from the extraction to the delayed-onset infection was 35 days (IQR 28–40; min 24–max 49). Younger age and longer surgical procedures seemed to be more often associated with this complication. Conclusion. Delayed-onset infections after third-molar extractions are relatively rare postoperative complications characterized by a swelling, usually with a purulent discharge. Patients should be informed of this possibility, which might develop even several weeks after the extraction.

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Yue Yi, Elaine Kueh, Annabelle Lai Siew Ying, Mandakini Mohan, and Rohit Kunnath Menon. "Prevalence of Postoperative Infection after Tooth Extraction: A Retrospective Study." International Journal of Dentistry 2021 (June 8, 2021): 1–6. http://dx.doi.org/10.1155/2021/6664311.

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The aim of the study was to identify the postoperative infection rates after tooth extraction in a university dental clinic and to identify the factors associated with an increased risk for postoperative infection. A retrospective study of case records of patients who underwent tooth extractions at the International Medical University’s Oral Health Centre (IMU-OHC) over a span of 6 years was conducted. Data on demography, patient-related factors, and treatment-related factors were extracted from the case records. A binary logistic regression analysis was performed to assess the odds ratio of a patient having a postoperative infection or not, comparing it with each variable. A total of 1821 extractions, including simple and complex extractions, were performed over 6 years. Only 25 (1.4%) of the cases were reported to have a postoperative infection. The complexity of the extraction was the only variable that significantly affected the occurrence of postoperative infection after extraction; more complex extractions were reported with higher rates of infection (binary logistic regression, OR = 2.03, p = 0.004). None of the other factors, including antibiotic prescription, had a significant influence on the occurrence of postoperative infection. The prevalence of postoperative infection after dental extractions was low in IMU-OHC, and prescribing antibiotics had no added advantage in the prevention of postoperative infection.

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Besançon, Clémence, Camille Chautard, Catherine Beaucaire, Sébastien Savoye, Paul Sardini, Martine Gérard, and Michael Descostes. "The Role of Barite in the Post-Mining Stabilization of Radium-226: A Modeling Contribution for Sequential Extractions." Minerals 10, no. 6 (May 29, 2020): 497. http://dx.doi.org/10.3390/min10060497.

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Barite is ubiquitous and known to incorporate 226Ra through the formation of a solid-solution. In U mining mill tailings, barite is one of the dominant sulfate-binding minerals. In such environments, sequential extractions are generally used to identify the U- and 226Ra-binding phases and their associated reactivity. To better decipher the main processes governing the behavior of 226Ra during such sequential extractions, a geochemical model was developed with PHREEQC mimicking the sequential extraction of U and 226Ra from Bois-Noirs Limouzat U mine tailings, France. The model results were compared with a dataset produced by an experimental sequential extraction from the same mine tailings and including data on the solids and selective extraction results with the major elements, U and 226Ra. The simulations reproduced the results of the experimental chemical extractions accurately, with iron oxyhydroxides being the major U binding phase. However, the modeling indicated rather that barite would be the main 226Ra binding phase, instead of the iron oxyhydroxides identified by the experimental extractions. This is consistent with the 226Ra concentration measured in pore water, but in disagreement with the direct interpretation of the sequential extractions. The direct interpretation disregarded the role of barite in the geochemical behavior of 226Ra because barite was not specifically targeted by any of the extraction steps. However, the modeling showed that the dissolution of 226Ra-binding barite by reactants would lead to a 226Ra redistribution among the clay minerals, resulting in a skew in the experimental results. Similar results were achieved by referring simply to the bulk mineralogy of the tailings. This study highlights the importance of considering the mineralogy, mineral reactivity and retention capacity for more realistic interpretation of sequential extractions. Moreover, this paper provides new perspectives on the long-term consequences of these mill tailings in which barite controls the geochemical behavior of the 226Ra.

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Gassama, Omar, Ndeye Astou Faye, Abdoul Aziz Diouf, Mouhamadou Mansour Niang, Magatte Mbaye, Daouda Ndour, Marie Edouard Faye Dieme, et al. "Foetal instrumental extractions (IE) at the maternity at Nabil Choucair Health Center (Senegal) from 2005 to 2016: epidemio-clinical and prognostic aspects." International Journal of Reproduction, Contraception, Obstetrics and Gynecology 7, no. 2 (January 23, 2018): 386. http://dx.doi.org/10.18203/2320-1770.ijrcog20180153.

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Background: The main objective was to take stock of practices on instrumental extractions at the maternity of Nabil Choucair Health Center.Methods: This was a prospective, descriptive study from 1 January 2005 to 31 April 2016. The collection was carried out through the data sheet completed on the basis of an analysis of files, the delivery register and the anaesthesia register of the operating room. The data was entered using the Sphinx software version 5 and the data analysis performed by Epi info version 3.5.Results: 240 instrumental extraction cases were compiled, and their frequency was 0.4%. The mean age of patients was 24.8 years. Obstetric vacuum was the most commonly used instrument (66.4%) and an episiotomy was performed in 73.6%. Maternal complications were dominated by simple perineal tears (6.2%).Conclusions: Instrumental extractions should be rehabilitated in our maternity facilities to combat the outbreak of the caesarean section. Instrumental extractions indications and techniques should be controlled to avoid complications

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Alsaegh, Mohammed Amjed, and Abdullah Wadullah Albadrani. "Pattern and Reasons for Permanent Tooth Extractions at Dental Clinics of the University of Science and Technology of Fujairah, UAE." Open Dentistry Journal 14, no. 1 (April 22, 2020): 143–49. http://dx.doi.org/10.2174/1874210602014010143.

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Objectives: To evaluate the pattern and reasons for permanent tooth extractions in an adult patient seeking free dental care at clinics of the University of Science and Technology of Fujairah, UAE. Methods: The current retrospective study involved patients who had a dental extraction in the student dental clinics of the University of Science and Technology of Fujairah. Data of 1000 randomly selected extractions were collected from the archive of the university dental clinics. Results: Males had more teeth extracted (88.3%) than females. The most frequent extraction (58.9%) was in individuals of 30-49 years old range. Dental caries was the major reason (44.6%) of extractions, followed by wisdom teeth related extraction (23.4%), periodontal disease (18.1), failure of endodontically treated teeth (8.7%), prosthetic reasons (2.6), orthodontic reasons (1.7%), and trauma (0.9%) respectively. The most extracted teeth were the maxillary posterior teeth (45.6%), followed by mandibular posterior teeth (38.2%); then, maxillary anterior teeth (8.8) and lastly, were the mandibular anterior teeth (7.4%). Caries was significantly more frequent in female gender (χ2= 250.126; p=.000), while the periodontal disease was more common in male gender (χ2 = 146.790; p=.000). Conclusion: Caries is the principal reason for tooth extractions, followed by wisdom teeth related problems and periodontal disease. There is an increasing percentage of tooth extraction due to periodontal disease with both aging and male gender. Caries was the more frequent reason for extraction in all quadrants, except the lower anterior teeth in which periodontal disease was the more frequent reason. Lastly, anterior teeth were retained in the oral cavity more than posterior teeth.

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Dissertations / Theses on the topic "Data extractions"

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Minh, Tuan Pham, Tomohiro Yoshikawa, Takeshi Furuhashi, and Kaita Tachibana. "Robust feature extractions from geometric data using geometric algebra." IEEE, 2009. http://hdl.handle.net/2237/13896.

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Dou, Lixin. "Applications of Bayesian inference methods to time series data analysis and hyperfine parameter extractions in Mössbauer spectroscopy." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0020/NQ45170.pdf.

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Dou, Lixin. "Applications of Bayesian inference methods to time series data analysis and hyperfine parameter extractions in Mossbauer spectroscopy." Thesis, University of Ottawa (Canada), 1999. http://hdl.handle.net/10393/8483.

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The Bayesian statistical inference theory is studied and applied to two problems in applied physics: spectral analysis and parameter estimation in time series data and hyperfine parameter extraction in Mossbauer spectroscopy. The applications to spectral analysis and parameter estimation for both single- and multiple-frequency signals are presented in detail. Specifically, the marginal posterior probabilities for the amplitudes and frequencies of the signals are obtained by using Gibbs sampling without performing the integration, no matter whether the variance of the noise is known or unknown. The best estimates of the parameters can be inferred from these probabilities together with the corresponding variances. When the variance of the noise is unknown, an estimate about the variance of the noise can also be made. Comparisons of our results have been made with results using the Fast Fourier Transformation (FFT) method as well as Bretthorst's method. The same numerical approach is applied to some complicated models and conditions, such as periodic but non-harmonic signals, signals with decay, and signals with chirp. Results demonstrate that even under these complicated conditions the Bayesian inference and Gibbs sampling can still give very accurate results with respect to the true result. Also through the use of the Bayesian inference methods it is possible to choose the most probable model based on known prior information of data, assuming a model space. The Bayesian inference theory is applied to hyperfine parameter extraction in Mossbauer spectroscopy for the first time. The method is a free-form model extraction approach and gives full error analysis of hyperfine parameter distributions. Two applications to quadrupole splitting distribution analysis in Fe-57 Mossbauer spectroscopy are presented. One involves a single site of Fe3+ and the other involves two sites for Fe3+ and Fe2+. In each case the method gives a unique solution to the distributions with arbitrary shape and is not sensitive to the elemental doublet parameters. The Bayesian inference theory is also applied to the hyperfine field distribution extraction. Because of the complexity of the elemental lineshape, all the other extraction methods can only use the first order perturbation sextet as the lineshape function. We use Blaes' exact lineshape model to extract the hyperfine field distribution. This is possible because the Bayesian inference theory is a free-form model extraction method. By using Blaes' lineshape function, different cases of orientations between the electric field gradient principle axis directions and the magnetic hyperfine field can be studied without making any approximations. As an example the ground state hyperfine field distribution of Fe65Ni35 Invar is extensively studied by using the method. Some very interesting features of the hyperfine field distribution are identified.

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Shakir, Amer, Muhammad Hammad, and Muhammad Kamran. "Comparative Analysis & Study of Android/iOS MobileForensics Tools." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44797.

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This report aims to draw a comparison between two commercial mobile forensics and recovery tools, Magnet AXIOM and MOBILedit. A thorough look at previously done studies was helpful to know what aspects of the data extractions must be compared and which areas are the most important ones to focus upon. This work focuses on how the data extracted from one tool compares with another and provides comprehensive extraction based on different scenarios, circumstances, and aspects. Performances of both tools are compared based on various benchmarks and criteria. This study has helped establish that MOBILedit has been able to outperform Magnet AXIOM on more data extraction and recovery aspects. It is a comparatively better tool to get your hands on.

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Sottovia, Paolo. "Information Extraction from data." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/242992.

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Data analysis is the process of inspecting, cleaning, extract, and modeling data with the intention of extracting useful information in order to support users in their decisions. With the advent of Big Data, data analysis was becoming more complicated due to the volume and variety of data. This process begins with the acquisition of the data and the selection of the data that is useful for the desiderata analysis. With such amount of data, also expert users are not able to inspect the data and understand if a dataset is suitable or not for their purposes. In this dissertation, we focus on five problems in the broad data analysis process to help users find insights from the data when they do not have enough knowledge about its data. First, we analyze the data description problem, where the user is looking for a description of the input dataset. We introduce data descriptions: a compact, readable and insightful formula of boolean predicates that represents a set of data records. Finding the best description for a dataset is computationally expensive and task-specific; we, therefore, introduce a set of metrics and heuristics for generating meaningful descriptions at an interactive performance. Secondly, we look at the problem of order dependency discovery, which discovers another kind of metadata that may help the user in the understanding of characteristics of a dataset. Our approach leverages the observation that discovering order dependencies can be guided by the discovery of a more specific form of dependencies called order compatibility dependencies. Thirdly, textual data encodes much hidden information. To allow this data to reach its full potential, there has been an increasing interest in extracting structural information from it. In this regard, we propose a novel approach for extracting events that are based on temporal co-reference among entities. We consider an event to be a set of entities that collectively experience relationships between them in a specific period of time. We developed a distributed strategy that is able to scale with the largest on-line encyclopedia available, Wikipedia. Then, we deal with the evolving nature of the data by focusing on the problem of finding synonymous attributes in evolving Wikipedia Infoboxes. Over time, several attributes have been used to indicate the same characteristic of an entity. This provides several issues when we are trying to analyze the content of different time periods. To solve it, we propose a clustering strategy that combines two contrasting distance metrics. We developed an approximate solution that we assess over 13 years of Wikipedia history by proving its flexibility and accuracy. Finally, we tackle the problem of identifying movements of attributes in evolving datasets. In an evolving environment, entities not only change their characteristics, but they sometimes exchange them over time. We proposed a strategy where we are able to discover those cases, and we also test our strategy on real datasets. We formally present the five problems that we validate both in terms of theoretical results and experimental evaluation, and we demonstrate that the proposed approaches efficiently scale with a large amount of data.

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Raza, Ali. "Test Data Extraction and Comparison with Test Data Generation." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/982.

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Testing an integrated information system that relies on data from multiple sources can be a challenge, particularly when the data is confidential. This thesis describes a novel test data extraction approach, called semantic-based test data extraction for integrated systems (iSTDE) that solves many of the problems associated with creating realistic test data for integrated information systems containing confidential data. iSTDE reads a consistent cross-section of data from the production databases, manipulates that data to obscure individual identities while still preserving overall semantic data characteristics that are critical to thorough system testing, and then moves that test data to an external test environment. This thesis also presents a theoretical study that compares test-data extraction with a competing technique, named test-data generation. Specifically, this thesis a) describes a comparison method that includes a comprehensive list of characteristics essential for testing the database applications organized into seven different areas, b) presents an analysis of the relative strengths and weaknesses of the different test-data creation techniques, and c) reports a number of specific conclusions that will help testers make appropriate choices.

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Wackersreuther, Bianca. "Efficient Knowledge Extraction from Structured Data." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-138079.

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Thelen, Andrea. "Optimized surface extraction from holographic data." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=980418798.

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Zhou, Yuanqiu. "Generating Data-Extraction Ontologies By Example." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd1115.pdf.

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Williams, Dean Ashley. "Combining data integration and information extraction." Thesis, Birkbeck (University of London), 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499152.

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Books on the topic "Data extractions"

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Frank, Lemke, ed. Self-organising data mining: Extracting knowledge from data. Dresden [u.a.]: J.-A. Müller, 2000.

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Developments in data extraction, management, and analysis. Hershey, PA: Information Science Reference, 2012.

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Mendelssohn, Roy. Comprehensive Ocean Data Set Extraction: User's guide. [La Jolla, Calif.]: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Southwest Fisheries Science Center, 1996.

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Paolo, Coletti, ed. Information extraction in finance. Southampton: WIT Press, 2008.

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Kipps, James R. Extracting tactical data from operation orders. Santa Monica, CA: Rand, 1992.

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Ouyahia, Lamine. Extracting data from several web sites. Oxford: Oxford Brookes University, 2002.

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Zhang, Wei Emma, and Quan Z. Sheng. Managing Data From Knowledge Bases: Querying and Extraction. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94935-2.

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Smedley, Ruth. Extracting hospital inpatient data for health boards. [S.l: The Author], 2003.

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Ward, Thomas E. Kinetic data extraction and analysis system for human gait. Dublin: University College Dublin, 1996.

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Liu, Huan. Feature Extraction, Construction and Selection: A Data Mining Perspective. Boston, MA: Springer US, 1998.

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Book chapters on the topic "Data extractions"

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Gupta, Rajeev. "Generic Key Value Extractions from Emails." In Big Data Analytics, 193–208. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-66665-1_13.

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Lohrum, Mark. "Forensic Extractions of Data from the Nokia N900." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 253–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35515-8_21.

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Lohrum, Mark. "Forensic Extractions of Data from the Nokia N900." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 89–103. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35515-8_8.

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Kuo, Bor-Chen, and Kuang-Yu Chang. "Regularized Feature Extractions and Support Vector Machines for Hyperspectral Image Data Classification." In Lecture Notes in Computer Science, 873–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552413_125.

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Wang, Haiyang, Xin Song, Yujia Liu, ChenGuang Chen, and Bin Zhou. "A Meta-path Based Graph Convolutional Network with Multi-scale Semantic Extractions for Heterogeneous Event Classification." In Advances in Knowledge Discovery and Data Mining, 459–71. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75762-5_37.

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Kiziak, Tanja. "New data on an old issue: Subject/object asymmetries in long extractions in German." In The Fruits of Empirical Linguistics II, 157–78. Berlin, New York: Mouton de Gruyter, 2009. http://dx.doi.org/10.1515/9783110216158.157.

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Meinel, Christoph, Justus Broß, Philipp Berger, and Patrick Hennig. "Data Extraction." In Blogosphere and its Exploration, 83–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44409-2_11.

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Tod, David. "Data Extraction." In Conducting Systematic Reviews in Sport, Exercise, and Physical Activity, 83–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12263-8_7.

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Jennings, W. Bryan. "DNA Extraction." In Phylogenomic Data Acquisition, 67–79. Boca Raton: Taylor & Francis, 2017.: CRC Press, 2016. http://dx.doi.org/10.1201/9781315181431-4.

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Zong, Chengqing, Rui Xia, and Jiajun Zhang. "Information Extraction." In Text Data Mining, 227–83. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0100-2_10.

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Conference papers on the topic "Data extractions"

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Freydenberger, Dominik D., Benny Kimelfeld, and Liat Peterfreund. "Joining Extractions of Regular Expressions." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3196959.3196967.

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Pham, Minh Tuan, Tomohiro Yoshikawa, Takeshi Furuhashi, and Kanta Tachibana. "Robust feature extractions from geometric data using geometric algebra." In 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2009. http://dx.doi.org/10.1109/icsmc.2009.5346869.

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Zheng, Gangtie, and Fai Ma. "Acoustic Emission: Data Analysis and Applications." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/cie-14664.

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Abstract Some applications and state-of-art of acoustic emission techniques are introduced in the present paper through an overview of publications in acoustic emission techniques. Attention is given to applications of acoustic emission techniques to the condition monitoring and damage feature extractions of reinforced concrete structures. With the use of numerical examples, major acoustic emission signal processing methods such as the wavelet transform, the Gabor transform, the bilinear time-frequency distribution, and the cepstral analysis are discussed.

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Trovati, Marcello, Philip Hodgson, Charlotte Hargreaves, Andrew David Baker, Lu Liu, and Nik Bessis. "Dependency Networks Extractions from Textual Sources in Criminology: An Initial Implementation." In 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService). IEEE, 2016. http://dx.doi.org/10.1109/bigdataservice.2016.19.

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Allen, Rob L. "Detailed Clastic Maps from Intense Log Data Extractions and Advanced Sedimentation Analysis." In SPE/AAPG Western Regional Meeting. Society of Petroleum Engineers, 2000. http://dx.doi.org/10.2118/62538-ms.

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Arima, Sumika, Huizhen Bu, Yuto Onuma, Kotaro Handa, and Takuya Nagata. "Feature Extractions from a High-dimension Low-samples Data for Multi-dimension Virtual Metrology." In 2019 Joint International Symposium on e-Manufacturing & Design Collaboration(eMDC) & Semiconductor Manufacturing (ISSM). IEEE, 2019. http://dx.doi.org/10.23919/emdc/issm48219.2019.9052136.

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Wang, Qian, Shengshan Hu, Kui Ren, Jingjun Wang, Zhibo Wang, and Minxin Du. "Catch me in the dark: Effective privacy-preserving outsourcing of feature extractions over image data." In IEEE INFOCOM 2016 - IEEE Conference on Computer Communications. IEEE, 2016. http://dx.doi.org/10.1109/infocom.2016.7524460.

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Whitlock, Brad J., Christopher Laganella, and Earl P. Duque. "Scoreboard: Management and Creation of In Situ and In Transit Data Extractions via Computational Steering." In AIAA Scitech 2021 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-1599.

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Rupapara, Vaibhav, Manideep Narra, Naresh Kumar Gonda, and Kaushika Thipparthy. "Relevant Data Node Extraction:A Web Data Extraction Method for Non Contagious Data." In 2020 5th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2020. http://dx.doi.org/10.1109/icces48766.2020.9137897.

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Khan, Mohd Jawed, and Pankaj Pratap Singh. "Road Extraction from Remotely Sensed Data: A Review." In Intelligent Computing and Technologies Conference. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.115.14.

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Up-to-date road networks are crucial and challenging in computer vision tasks. Road extraction is yet important for vehicle navigation, urban-rural planning, disaster relief, traffic management, road monitoring and others. Road network maps facilitate a great number of applications in our everyday life. Therefore, a systematic review of deep learning approaches applied to remotely sensed imagery for road extraction is conducted in this paper. Four main types of deep learning approaches, namely, the GANs model, deconvolutional networks, FCNs, and patch-based CNNs models are presented in this paper. We also compare these various deep learning models applied to remotely sensed imagery to show their performances in extracting road parts from high-resolution remote sensed imagery. Later future research directions and research gaps are described.

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Reports on the topic "Data extractions"

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McLean, Michael L., Newsom Sr., and Benjamin. Extractions of Garment Manufacturing Data from 3D Whole Body Scans. Fort Belvoir, VA: Defense Technical Information Center, February 1998. http://dx.doi.org/10.21236/ada347501.

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Gates, Allison, Michelle Gates, Shannon Sim, Sarah A. Elliott, Jennifer Pillay, and Lisa Hartling. Creating Efficiencies in the Extraction of Data From Randomized Trials: A Prospective Evaluation of a Machine Learning and Text Mining Tool. Agency for Healthcare Research and Quality (AHRQ), August 2021. http://dx.doi.org/10.23970/ahrqepcmethodscreatingefficiencies.

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Background. Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We prospectively evaluated an online machine learning and text mining tool’s ability to (a) automatically extract data elements from randomized trials, and (b) save time compared with manual extraction and verification. Methods. For 75 randomized trials published in 2017, we manually extracted and verified data for 21 unique data elements. We uploaded the randomized trials to ExaCT, an online machine learning and text mining tool, and quantified performance by evaluating the tool’s ability to identify the reporting of data elements (reported or not reported), and the relevance of the extracted sentences, fragments, and overall solutions. For each randomized trial, we measured the time to complete manual extraction and verification, and to review and amend the data extracted by ExaCT (simulating semi-automated data extraction). We summarized the relevance of the extractions for each data element using counts and proportions, and calculated the median and interquartile range (IQR) across data elements. We calculated the median (IQR) time for manual and semiautomated data extraction, and overall time savings. Results. The tool identified the reporting (reported or not reported) of data elements with median (IQR) 91 percent (75% to 99%) accuracy. Performance was perfect for four data elements: eligibility criteria, enrolment end date, control arm, and primary outcome(s). Among the top five sentences for each data element at least one sentence was relevant in a median (IQR) 88 percent (83% to 99%) of cases. Performance was perfect for four data elements: funding number, registration number, enrolment start date, and route of administration. Among a median (IQR) 90 percent (86% to 96%) of relevant sentences, pertinent fragments had been highlighted by the system; exact matches were unreliable (median (IQR) 52 percent [32% to 73%]). A median 48 percent of solutions were fully correct, but performance varied greatly across data elements (IQR 21% to 71%). Using ExaCT to assist the first reviewer resulted in a modest time savings compared with manual extraction by a single reviewer (17.9 vs. 21.6 hours total extraction time across 75 randomized trials). Conclusions. Using ExaCT to assist with data extraction resulted in modest gains in efficiency compared with manual extraction. The tool was reliable for identifying the reporting of most data elements. The tool’s ability to identify at least one relevant sentence and highlight pertinent fragments was generally good, but changes to sentence selection and/or highlighting were often required.

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Griffin, Andrew, Sean Griffin, Kristofer Lasko, Megan Maloney, S. Blundell, Michael Collins, and Nicole Wayant. Evaluation of automated feature extraction algorithms using high-resolution satellite imagery across a rural-urban gradient in two unique cities in developing countries. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40182.

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Feature extraction algorithms are routinely leveraged to extract building footprints and road networks into vector format. When used in conjunction with high resolution remotely sensed imagery, machine learning enables the automation of such feature extraction workflows. However, many of the feature extraction algorithms currently available have not been thoroughly evaluated in a scientific manner within complex terrain such as the cities of developing countries. This report details the performance of three automated feature extraction (AFE) datasets: Ecopia, Tier 1, and Tier 2, at extracting building footprints and roads from high resolution satellite imagery as compared to manual digitization of the same areas. To avoid environmental bias, this assessment was done in two different regions of the world: Maracay, Venezuela and Niamey, Niger. High, medium, and low urban density sites are compared between regions. We quantify the accuracy of the data and time needed to correct the three AFE datasets against hand digitized reference data across ninety tiles in each city, selected by stratified random sampling. Within each tile, the reference data was compared against the three AFE datasets, both before and after analyst editing, using the accuracy assessment metrics of Intersection over Union and F1 Score for buildings and roads, as well as Average Path Length Similarity (APLS) to measure road network connectivity. It was found that of the three AFE tested, the Ecopia data most frequently outperformed the other AFE in accuracy and reduced the time needed for editing.

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Gallis, Michail A., and Edward Stanley Piekos. Accelerating DSMC data extraction. Office of Scientific and Technical Information (OSTI), October 2006. http://dx.doi.org/10.2172/922066.

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Nurre, Joseph H. Automate Information Extraction from Scan Data. Fort Belvoir, VA: Defense Technical Information Center, November 1998. http://dx.doi.org/10.21236/ada362095.

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Toutin, Th. Road Extraction from Stereo RADARSAT Data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/219519.

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Youtsey, Wesley J., and Robert L. Woodyard. Bathymetric Data Set Extraction Program. Users Guide. Fort Belvoir, VA: Defense Technical Information Center, November 1993. http://dx.doi.org/10.21236/ada274761.

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Bradtmiller, Bruce. Automating Information Extraction from 3-D Scan Data. Fort Belvoir, VA: Defense Technical Information Center, October 1998. http://dx.doi.org/10.21236/ada361314.

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Chang, Kevin C., Truman Shuck, and Govind Kabra. Web-Scale Search-Based Data Extraction and Integration. Fort Belvoir, VA: Defense Technical Information Center, October 2011. http://dx.doi.org/10.21236/ada554205.

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Jones, Charles H. Automated Extraction of Data Display Configuration From Telemetry Applications. Fort Belvoir, VA: Defense Technical Information Center, May 2004. http://dx.doi.org/10.21236/ada426294.

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