Relevant bibliographies by topics / Given data

Academic literature on the topic 'Given data'

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Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Given data"

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Zadelaar, Jacqueline N., Joost A. Agelink van Rentergem, and Hilde M. Huizenga. "Univariate comparisons given aggregated normative data." Clinical Neuropsychologist 31, no. 6-7 (July 5, 2017): 1155–72. http://dx.doi.org/10.1080/13854046.2017.1348542.

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Plischke, Elmar, Emanuele Borgonovo, and Curtis L. Smith. "Global sensitivity measures from given data." European Journal of Operational Research 226, no. 3 (May 2013): 536–50. http://dx.doi.org/10.1016/j.ejor.2012.11.047.

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McCormick, Tyler H. "The "Given Data" Paradigm Undermines Both Cultures." Observational Studies 7, no. 1 (2021): 157–59. http://dx.doi.org/10.1353/obs.2021.0002.

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Stensholt, Eivind. "Regular matrix polynomials with given spectral data." Linear Algebra and its Applications 121 (August 1989): 666–73. http://dx.doi.org/10.1016/s0024-3795(16)30317-2.

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Zhang, Li-Chun. "Generalised Regression Estimation Given Imperfectly Matched Auxiliary Data." Journal of Official Statistics 37, no. 1 (March 1, 2021): 239–55. http://dx.doi.org/10.2478/jos-2021-0010.

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Abstract Generalised regression estimation allows one to make use of available auxiliary information in survey sampling. We develop three types of generalised regression estimator when the auxiliary data cannot be matched perfectly to the sample units, so that the standard estimator is inapplicable. The inference remains design-based. Consistency of the proposed estimators is either given by construction or else can be tested given the observed sample and links. Mean square errors can be estimated. A simulation study is used to explore the potentials of the proposed estimators.
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Hu, Zhengbing, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko, and Viktoriia O. Samitova. "Fuzzy Clustering Data Given in the Ordinal Scale." International Journal of Intelligent Systems and Applications 9, no. 1 (January 8, 2017): 67–74. http://dx.doi.org/10.5815/ijisa.2017.01.07.

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Mccloughan, Patrick, and Esmaiel Abounoori. "How to estimate market concentration given grouped data." Applied Economics 35, no. 8 (May 20, 2003): 973–83. http://dx.doi.org/10.1080/0003648032000050603.

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Hushagen, Sam. "Sense Data and the Romantic Myth of the Given." Wordsworth Circle 53, no. 3 (June 1, 2022): 311–33. http://dx.doi.org/10.1086/720738.

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PFANNKUCH, MAXINE, and AMANDA RUBICK. "AN EXPLORATION OF STUDENTS’ STATISTICAL THINKING WITH GIVEN DATA." STATISTICS EDUCATION RESEARCH JOURNAL 1, no. 2 (December 29, 2002): 4–21. http://dx.doi.org/10.52041/serj.v1i2.562.

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This paper examines how two twelve-year-old students built up their recognition and understanding of relationships in a set of data. Using a small multivariate dataset created by Watson, Collis, Callingham and Moritz (1995), the students conducted an investigation of their choice in a pencil-and-paper environment. The students’ thinking across the three representations of cards, tables and graphs is analysed from the perspectives of transnumeration, consideration of variation, reasoning with statistical models, and integrating the statistical with the contextual, which were identified as fundamental statistical thinking elements in empirical enquiry in the framework of Wild and Pfannkuch (1999). The ways of thinking within each element across the representations are identified. In the analysis, references are also made to the types of statistical thinking present in the other ten students in the study. From the analysis we identified five issues that should be considered for determining how students construct meanings from data. They are: prior contextual and statistical knowledge; thinking at a higher level than constructed representations; actively representing and construing; the intertwinement of local and global thinking; and the changing statistical thinking dialogue across the representations. First published December 2002 at Statistics Education Research Journal: Archives
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YOSHIDA, Kotaro, Hidefumi WAKAMATSU, Eiji MORINAGA, Seichiro TSUTSUMI, and Takahiro KUBO. "Design of developable surfaces using the given data points." Journal of Advanced Mechanical Design, Systems, and Manufacturing 15, no. 5 (2021): JAMDSM0056. http://dx.doi.org/10.1299/jamdsm.2021jamdsm0056.

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Dissertations / Theses on the topic "Given data"

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McLaughlin, N. R. "Robust multimodal person identification given limited training data." Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.579747.

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Abstract This thesis presents a novel method of audio-visual fusion, known as multi- modal optimal feature fusion (MOFF), for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowl- edge about the corruption. Furthermore, it is assumed there is a limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature rep- resentation and a modified cosine similarity are introduced for combining and comparing bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Similarity-based optimal feature selection and multi- condition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Low-level feature fusion is performed using optimal feature selection, which automatically changes the weighting given to each modality based on the level of corruption. The framework for robust person identification is also applied to noise robust speaker identification, given very limited training data. Experiments have been carried out on a bimodal data set created from the SPIDRE speaker recogni- tion database and AR face recognition database, with variable noise corruption of speech and occlusion in the face images. Combining both modalities using MOFF, leads to significantly improved identification accuracy compared to the component unimodal systems, even with simultaneous corruption of both modal- ities. A novel piecewise-constant illumination model (PCIlVI) is then introduced for illumination invariant facial recognition. This method can be used given a single training facial image for each person, and assuming no prior knowledge of the illumination conditions of both the training and testing images. Small areas of the face are represented using magnitude Fourier features, which takes advan- tage of the shift-invariance of the magnitude Fourier representation, to increase robustness to small misalignment errors and small facial expression changes. Fi- nally, cosine similarity is used as an illumination invariant similarity measure, to compare small facial areas. Experiments have been carried out on the YaleB, ex- tended YaleB and eMU-PIE facial illumination databases. Facial identification accuracy using PCIlVI is comparable to or exceeds that of the literature.
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Friesch, Pius. "Generating Training Data for Keyword Spotting given Few Samples." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254960.

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Speech recognition systems generally need a large quantity of highly variable voice and recording conditions in order to produce robust results. In the specific case of keyword spotting, where only short commands are recognized instead of large vocabularies, the resource-intensive task of data acquisition has to be repeated for each keyword individually. Over the past few years, neural methods in speech synthesis and voice conversion made tremendous progress and generate samples that are realistic to the human ear. In this work, we explore the feasibility of using such methods to generate training data for keyword spotting methods. In detail, we want to evaluate if the generated samples are indeed realistic or only sound so and if a model trained on these generated samples can generalize to real samples. We evaluated three neural network speech synthesis and voice conversion techniques : (1) Speaker Adaptive VoiceLoop, (2) Factorized Hierarchical Variational Autoencoder (FHVAE), (3) Vector Quantised-Variational AutoEncoder (VQVAE). These three methods are evaluated as data augmentation or data generation techniques on a keyword spotting task. The performance of the models is compared to a baseline of changing the pitch, tempo, and speed of the original sample. The experiments show that using the neural network techniques can provide an up to 20% relative accuracy improvement on the validation set. The baseline augmentation technique performs at least twice as good. This seems to indicate that using multi-speaker speech synthesis or voice conversation naively does not yield varied or realistic enough samples.
Taligenkänningssystem behöver generellt en stor mängd träningsdata med varierande röstoch inspelningsförhållanden för att ge robusta resultat. I det specifika fallet med nyckelordsidentifiering, där endast korta kommandon känns igen i stället för stora vokabulärer, måste resurskrävande datainsamling göras för varje sökord individuellt. Under de senaste åren har neurala metoder i talsyntes och röstkonvertering gjort stora framsteg och genererar tal som är realistiskt för det mänskliga örat. I det här arbetet undersöker vi möjligheten att använda sådana metoder för att generera träningsdata för nyckelordsidentifiering. I detalj vill vi utvärdera om det genererade träningsdatat verkligen är realistiskt eller bara låter så, och om en modell tränad på dessa genererade exempel generaliserar väl till verkligt tal. Vi utvärderade tre metoder för neural talsyntes och röstomvandlingsteknik: (1) Speaker Adaptive VoiceLoop, (2) Factorized Hierarchical Variational Autoencoder (FHVAE), (3) Vector Quantised-Variational AutoEncoder (VQVAE).Dessa tre metoder används för att antingen generera träningsdata från text (talsyntes) eller att berika ett befintligt dataset för att simulera flera olika talare med hjälp av röstkonvertering, och utvärderas i ett system för nyckelordsidentifiering. Modellernas prestanda jämförs med en baslinje baserad på traditionell signalbehandling där tonhöjd och tempo varieras i det ursprungliga träningsdatat. Experimenten visar att man med hjälp av neurala nätverksmetoder kan ge en upp till 20% relativ noggrannhetsförbättring på valideringsuppsättningen jämfört med ursprungligt träningsdata. Baslinjemetoden baserad på signalbehandling ger minst dubbelt så bra resultat. Detta tycks indikera att användningen av talsyntes eller röstkonvertering med flera talare inte ger tillräckligt varierade eller representativa träningsdata.
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Fan, Hang. "Species Tree Likelihood Computation Given SNP Data Using Ancestral Configurations." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385995244.

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Ren, Chunfeng. "LATENT VARIABLE MODELS GIVEN INCOMPLETELY OBSERVED SURROGATE OUTCOMES AND COVARIATES." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3473.

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Latent variable models (LVMs) are commonly used in the scenario where the outcome of the main interest is an unobservable measure, associated with multiple observed surrogate outcomes, and affected by potential risk factors. This thesis develops an approach of efficient handling missing surrogate outcomes and covariates in two- and three-level latent variable models. However, corresponding statistical methodologies and computational software are lacking efficiently analyzing the LVMs given surrogate outcomes and covariates subject to missingness in the LVMs. We analyze the two-level LVMs for longitudinal data from the National Growth of Health Study where surrogate outcomes and covariates are subject to missingness at any of the levels. A conventional method for efficient handling of missing data is to reexpress the desired model as a joint distribution of variables, including the surrogate outcomes that are subject to missingness conditional on all of the covariates that are completely observable, and estimate the joint model by maximum likelihood, which is then transformed to the desired model. The joint model, however, identifies more parameters than desired, in general. The over-identified joint model produces biased estimates of LVMs so that it is most necessary to describe how to impose constraints on the joint model so that it has a one-to-one correspondence with the desired model for unbiased estimation. The constrained joint model handles missing data efficiently under the assumption of ignorable missing data and is estimated by a modified application of the expectation-maximization (EM) algorithm.
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Cao, Haoliang. "Automating Question Generation Given the Correct Answer." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287460.

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In this thesis, we propose an end-to-end deep learning model for a question generation task. Given a Wikipedia article written in English and a segment of text appearing in the article, the model can generate a simple question whose answer is the given text segment. The model is based on an encoder-decoder architecture. Our experiments show that a model with a fine-tuned BERT encoder and a self-attention decoder give the best performance. We also propose an evaluation metric for the question generation task, which evaluates both syntactic correctness and relevance of the generated questions. According to our analysis on sampled data, the new metric is found to give better evaluation compared to other popular metrics for sequence to sequence tasks.
I den här avhandlingen presenteras en djup neural nätverksmodell för en frågeställningsuppgift. Givet en Wikipediaartikel skriven på engelska och ett textsegment i artikeln kan modellen generera en enkel fråga vars svar är det givna textsegmentet. Modellen är baserad på en kodar-avkodararkitektur (encoderdecoder architecture). Våra experiment visar att en modell med en finjusterad BERT-kodare och en självuppmärksamhetsavkodare (self-attention decoder) ger bästa prestanda. Vi föreslår också en utvärderingsmetrik för frågeställningsuppgiften, som utvärderar både syntaktisk korrekthet och relevans för de genererade frågorna. Enligt vår analys av samplade data visar det sig att den nya metriken ger bättre utvärdering jämfört med andra populära metriker för utvärdering.
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GIOIA, PAOLA. "Towards more accurate measures of global sensitivity analysis. Investigation of first and total order indices." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/45695.

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A new technique for estimating variance–based total sensitivity indices from given data is developed. It is also develped a new approach for the estimation of the first order effects given a specific sample design. This method adopts the RBD approach published by Tarantola et al., (2007) for the computation of first order sensitivity indices in association to Quasi–Random numbers.
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Liu, Fenglei. "Detection and estimation of connection splice events in fiber optics given noisy OTDR data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0009/MQ36049.pdf.

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Stoor, John-Bernhard. "Utveckling av GUI utifrån en given affärsprocess." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205667.

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Preem verkar inom drivmedelsbranschen som styrs av en mycket hög omsättning med förhållandevis små marginaler. Det är därför viktig med en väl fungerande lagerkontroll. Det man idag är ute efter är en ökad precision i lageruppföljningen och därmed behövs ett nytt systemstöd till detta. Jag fick i min roll hos Preem uppgiften att titta närmre på GUI och processerna bakom. Det resulterade i denna rapport med ett framtaget förslag på användargränssnittet till det nya systemet och dess affärsprocesser som är kopplat till detta. Arbetet fokuserar på hur de två framställs i förhållande till varandra och vilka metoder som används för att konstruera dessa. Arbetet inkluderar illustrationer av as-is och to-be processmodeller enligt BPMN specifikation, wireframes och en sitemap. Denna rapport visar ett förslag på ett sammanfört system och ett intuitivare GUI med nya processer bakom, för just Preem, och hur balansgången går mellan att skapa affärsprocesser och ett grafiskt användargränssnitt ur varandra, beroende av vilka som är involverade i projektet.
Preem is a Swedish company that operates in the oil industry, which is controlled by very high sales and with relatively small margins. It’s therefore essential with a well working stock control. Today they are looking for a better way of monitoring the stock with a higher precision and therefore they need a new system for that. My role at Preem was to take a closer look at the GUI and the processes behind that. It resulted in this thesis that includes the user interface for the new system and the business processes that are linked to this. The work will focus on how these two methods are produced in relation to each other, and the methods that are used to construct them. The thesis includes illustrations of as-is and to-be process models of the BPMN specification, wireframes and a sitemap. This report shows a proposal of an integrating system and an intuitive GUI with new processes, at Preem, and how the balance is between creating business processes and a graphical user interface out of each other, depending on the people who are involved in the project.
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Subramaniam, Rajesh. "Exploring Frameworks for Rapid Visualization of Viral Proteins Common for a Given Host." Thesis, North Dakota State University, 2019. https://hdl.handle.net/10365/31716.

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Viruses are unique organisms that lack the protein machinery necessary for its propagation (like polymerase) yet possess other proteins that facilitate its propagation (like host cell anchoring proteins). This study explores seven different frameworks to assist rapid visualization of proteins that are common to viruses residing in a given host. The proposed frameworks rely only on protein sequence information. It was found that the sequence similarity-based framework with an associated profile hidden Markov model was a better tool to assist visualization of proteins common to a given host than other proposed frameworks based only on amino acid composition or other amino acid properties. The lack of knowledge of profile hidden Markov models for many protein structures limit the utility of the proposed protein sequence similarity-based framework. The study concludes with an attempt to extrapolate the utility of the proposed framework to predict viruses that may pose potential human health risks.
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George, Andrew Winston. "A Bayesian analysis for the mapping of a quantitative trait locus given half-sib data." Thesis, Queensland University of Technology, 1998.

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Books on the topic "Given data"

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Euclid, ed. Dedomena: Euclid's Data, or, The importance of being given. Copenhagen: Museum Tusculanum Press, 2003.

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Zingg, D. W. A method of smooth bivariate interpolation for data given on a generalized curvilinear grid. [S.l.]: [s.n.], 1992.

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Wilkins, David C. Sociopathic knowledge bases: Correct knowledge can be harmful even given unlimited computation. Urbana, Illinois: Department of Computer Science, University of Illinois, 1989.

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Folland, Chris. Representativeness, data gaps and uncertainties in climate observations: (invited scientific lecture given by Chris Folland to the Thirteenth WMO Congress, 21 May 1999). Geneva: World Meteorological Organization, 2000.

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V, Di Gesù, Scarsi L, and Crane P, eds. Selected topics on data analysis in astronomy: General lectures given at the II Workshop on Data Analysis in Astronomy, Erice, Italy, April 20-30, 1986. Singapore: World Scientific, 1987.

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Grigor'ev, Anatoliy, and Evgeniy Isaev. Methods and algorithms of data processing. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1032305.

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The tutorial deals with selected methods and algorithms of data processing, the sequence of solving problems of processing and analysis of data to create models behavior of the object taking into account all the components of its mathematical model. Describes the types of technological methods for the use of software and hardware for solving problems in this area. The algorithms of distributions, regressions vremenny series, transform them with the aim of obtaining mathematical models and prediction of the behavior information and economic systems (objects). The second edition is supplemented by materials that are in demand by researchers in the part of the correct use of clustering algorithms. Are elements of the classification algorithms to identify their capabilities, strengths and weaknesses. Are the procedures of justification and verify the adequacy of the results of the cluster analysis, conducted a comparison and evaluation of different clustering techniques, given information about visualization of multidimensional data and examples of practical application of clustering algorithms. Meets the requirements of Federal state educational standards of higher education of the last generation. For students of economic specialties, specialists, and graduate students.
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Logunova, Oksana, Petr Romanov, and Elena Il'ina. Processing of experimental data on a computer. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1064882.

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The textbook provides information about the main methods and tools for automating computational processes used in data processing; methods for representing and generating models of experimental data; data models and classification of processing tasks; and the organization of the user interface in automated systems for processing experimental data. Contains structured chapters on the specifics of experimental research. The features of using software for processing experimental data are clearly and logically described. Theoretical material and basic algorithms for processing experimental data used in industrial statistics are presented. Examples of processing experimental data in the field of metallurgy and management in higher education are given. Meets the requirements of the Federal state educational standards of higher education of the latest generation. For students and postgraduates of higher educational institutions.
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Toronto), Conference on Editorial Problems (20th 1984 University of. Editing, publishing, and computer technology: Papers given at the twentieth annual Conference on Editorial Problems, University of Toronto, 2-3 November 1984. New York: AMS Press, 1988.

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Ilson, Robert. Assembling, analysing, and using a corpus of authentic language: A lecture given on the Survey of English Usage at the Linguistics Institute of the Hungarian Academy of Sciences on 2 September, 1988. [Budapest]: Magyar Tudományos Akadémia Nyelvtudományi Intézete, Institutum Linguisticum Academiae Scientiarum Hungaricae, 1991.

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Alberto, Ferrari, ed. Microsoft PowerPivot for Excel 2010: Give your data meaning. Redmond, Wash: Microsoft, 2011.

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Book chapters on the topic "Given data"

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Vapnik, Vladimir. "Estimation of Functional Values at Given Points." In Estimation of Dependences Based on Empirical Data, 312–50. New York, NY: Springer New York, 2006. http://dx.doi.org/10.1007/0-387-34239-7_10.

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Subhashi, Charitha, and Malka Halgamuge. "Selecting Suitable Plants for a Given Area using Data Analysis Approaches." In Data Science and Big Data Analytics in Smart Environments, 172–96. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9780367814397-9.

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Lions, J. L. "Remarks on systems with incompletely given initial data and incompletely given part of the boundary." In Lecture Notes in Mathematics, 239–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/bfb0085483.

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Varma, U. Abhinand, D. V. Rakesh Reddy, Prasanth Paraselli, and Joy Mustafi. "Answering Predictive Questions in Natural Language Based on Given Data for Forecasting." In Data Management, Analytics and Innovation, 313–27. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5619-7_22.

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Bartkowiak, Anna, and Krystyna Ziętak. "Backprojection of data vectors using a given covariance matrix." In Advanced Computer Systems, 27–38. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4419-8530-9_2.

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Gimadi, Edward Kh, and Ekaterina Yu Shin. "On Given Diameter MST Problem on Random Input Data." In Mathematical Optimization Theory and Operations Research, 30–38. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33394-2_3.

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Ortega-Jiménez, Patricia, Franco Pellerey, Miguel A. Sordo, and Alfonso Suárez-Llorens. "Note on Efron’s Monotonicity Property Under Given Copula Structures." In Building Bridges between Soft and Statistical Methodologies for Data Science, 303–10. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15509-3_40.

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Montesinos López, Osval Antonio, Abelardo Montesinos López, and Jose Crossa. "Preprocessing Tools for Data Preparation." In Multivariate Statistical Machine Learning Methods for Genomic Prediction, 35–70. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89010-0_2.

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AbstractThis data preparation chapter is of paramount importance for implementing statistical machine learning methods for genomic selection. We present the basic linear mixed model that gives rise to BLUE and BLUP and explain how to decide when to use fixed or random effects that give rise to best linear unbiased estimates (BLUE or BLUEs) and best linear unbiased predictors (BLUP or BLUPs). The R codes for fitting linear mixed model for the data are given in small examples. We emphasize tools for computing BLUEs and BLUPs for many linear combinations of interest in genomic-enabled prediction and plant breeding. We present tools for cleaning, imputing, and detecting minor and major allele frequency computation, marker recodification, frequency of heterogeneous, frequency of NAs, and three methods for computing the genomic relationship matrix. In addition, scaling and data compression of inputs are important in statistical machine learning. For a more extensive description of linear mixed models, see Chap. 10.1007/978-3-030-89010-0_5.
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Nawalkar, Neha, Vahida Z. Attar, and Shrida P. Kalamkar. "Automated ICD-9 Medical Code Assignment from Given Free Text Using Deep Learning Approach." In Advances in Data and Information Sciences, 317–27. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5689-7_28.

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Brazdil, Pavel, Jan N. van Rijn, Carlos Soares, and Joaquin Vanschoren. "Automating Data Science." In Metalearning, 269–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-67024-5_14.

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AbstractIt has been observed that, in data science, a great part of the effort usually goes into various preparatory steps that precede model-building. The aim of this chapter is to focus on some of these steps. A comprehensive description of a given task to be resolved is usually supplied by the domain expert. Techniques exist that can process natural language description to obtain task descriptors (e.g., keywords), determine the task type, the domain, and the goals. This in turn can be used to search for the required domain-specific knowledge appropriate for the given task. In some situations, the data required may not be available and a plan needs to be elaborated regarding how to get it. Although not much research has been done in this area so far, we expect that progress will be made in the future. In contrast to this, the area of preprocessing and transformation has been explored by various researchers. Methods exist for selection of instances and/or elimination of outliers, discretization and other kinds of transformations. This area is sometimes referred to as data wrangling. These transformations can be learned by exploiting existing machine learning techniques (e.g., learning by demonstration). The final part of this chapter discusses decisions regarding the appropriate level of detail (granularity) to be used in a given task. Although it is foreseeable that further progress could be made in this area, more work is needed to determine how to do this effectively.
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Conference papers on the topic "Given data"

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Chojnacki, W., M. Brooks, A. van den Hengel, and D. Gawley. "Estimating Vision Parameters given Data with Covariances." In British Machine Vision Conference 2000. British Machine Vision Association, 2000. http://dx.doi.org/10.5244/c.14.19.

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Syrkov, A. "Enhancing of Bridge Management Given Failures Data." In IABSE Symposium, Wroclaw 2020: Synergy of Culture and Civil Engineering – History and Challenges. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2020. http://dx.doi.org/10.2749/wroclaw.2020.1173.

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<p>It has been observed a tendency towards an increasing in the number of failures of road and pedestrian bridges worldwide, as well as growing of their consequences for human life and health in the past decades. Some results of these collapses analysis, performed by the IABSE task group TG1.5, are given in the article. Growing of the share of failures that occurred during the operation of bridges in the presence of traffic on the carriageway and/or under the spans that collapsed was noted. At the same time, the most part of operated bridges failures occurred due to presence of unrecognized hidden defects. The main principles of new method developed to enhance monitoring and rehabilitation measures prioritizing are described in the article as an example for a risk group including a big sample of simple pre-stressed main girders from the bridge stock with limited budget. The relevant actual hazards, warning signs, triggers, defects, failure modes and fault tree are given. Some results of the new method implementation enhancing the BMS activities are presented.</p>
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Feng, Junkai, Saiping Zhang, Fuzheng Yang, and Shuai Wan. "Rate-Distortion Optimization for Video Coding under Given Computational Complexity." In 2017 Data Compression Conference (DCC). IEEE, 2017. http://dx.doi.org/10.1109/dcc.2017.41.

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Lavangnananda, Kittichai, and Muhammad Aslam HemmatQachmas. "Finding Overlapping Clusters in a Highly Connected Graph from a Given Difference Density." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378329.

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Asudeh, Abolfazl, Zhongjun Jin, and H. V. Jagadish. "Assessing and Remedying Coverage for a Given Dataset." In 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE, 2019. http://dx.doi.org/10.1109/icde.2019.00056.

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Gershman, Anatole, Eugene Fink, Bin Fu, and Jaime G. Carbonell. "Analysis of uncertain data: Evaluation of given hypotheses." In 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2009. http://dx.doi.org/10.1109/icsmc.2009.5346325.

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Tao Xiang and Shaogang Gong. "Visual learning given sparse data of unknown complexity." In Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. IEEE, 2005. http://dx.doi.org/10.1109/iccv.2005.250.

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Zhang, Yao, and B. Aditya Prakash. "Scalable Vaccine Distribution in Large Graphs given Uncertain Data." In CIKM '14: 2014 ACM Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2661829.2662088.

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Herault, Thomas, Julien Herrmann, Loris Marchal, and Yves Robert. "Determining the Optimal Redistribution for a Given Data Partition." In 2014 IEEE 13th International Symposium on Parallel and Distributed Computing (ISPDC). IEEE, 2014. http://dx.doi.org/10.1109/ispdc.2014.16.

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Haunert, Jan-Henrik, and Benedikt Budig. "An algorithm for map matching given incomplete road data." In the 20th International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2424321.2424402.

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Reports on the topic "Given data"

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Pantoja, Tomás, and Signe Flottorp. Does providing healthcare professionals with data about their performance improve their practice? SUPPORT, 2017. http://dx.doi.org/10.30846/170212.

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Audit and feedback is commonly used as a strategy to improve professional practice. It appears logical that healthcare professionals would be prompted to modify their practice if given feedback that their clinical practice was inconsistent with that of their peers or accepted guidelines.
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Emery, Benjamin. National Sediment Placement Data Viewer users guide. Engineer Research and Development Center (U.S.), July 2022. http://dx.doi.org/10.21079/11681/44700.

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This US Army Corps of Engineers (USACE) Regional Sediment Management (RSM) technical note serves as a user’s guide for the RSM National Sediment Placement Data Viewer. This application was created utilizing over 20 yr* of detailed and verified USACE dredging data, giving users an interactive web-based tool that takes these datasets and displays them on a national map, viewable at the district or project scale. The Data Viewer will quantify the total cubic yards dredged, disposed, and/or beneficially used based on the user selected parameters. Detailed information on the datasets utilized and the verification processes followed to create this application can be found in ERDC/TN RSM-22-XX, USACE Navigation Sediment Placement: An RSM Program Database (1998 – 2019) (Elko et al. 2022). This technical note attempts to define each of the inputs/outputs given from the Data Viewer and then provide a step-by-step example of utilizing the Data Viewer, accessed here: https://www.arcgis.com/apps/MapSeries/index.html?appid=0ea8fc0a956f46068428c862e7497233
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Sible, Jill, Erica Echols, Kasey Richardson, and Hao Wang. Using Data to Fuel Inclusive Excellence at Virginia Tech. Ithaka S+R, May 2021. http://dx.doi.org/10.18665/sr.315527.

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In Fall 2020, the American Talent Initiative (ATI), an alliance of high-graduation-rate colleges and universities committed to expanding access and opportunity for low- and middle-income students, established its newest community of practice (CoP) focused on academic equity. Together, the 37 CoP members explore topics related to creating equitable academic communities. One such area of focus is how institutions can more effectively utilize data to enhance equity-related projects. In January 2021, members participated in a webinar discussion on this topic, during which CoP representatives presented on how they have leveraged data in their academic equity work. This case study builds on a presentation given by Dr. Jill Sible, Associate Vice Provost for Undergraduate Education and Professor of Biological Sciences at Virginia Tech, titled, “Using data to fuel inclusive excellence at Virginia Tech.”
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Borchmann, Daniel. Model Exploration by Confidence with Completely Specified Counterexamples. Technische Universität Dresden, 2013. http://dx.doi.org/10.25368/2022.201.

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We present an extensions of our previous work on axiomatizing confident general concept inclusions in given finite interpretations. Within this extension we allow external experts to interactively provide counterexamples to general concept inclusions with otherwise enough confidence in the given data. This extensions allows us to distinguish between erroneous counterexamples in the data and rare, but valid counterexamples.
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Wetzel, Deborah, Fátima Cartaxo, Ricardo Poppi, and Mariano Lafuente. Data-driven Digital Innovation to Strengthen Integrity: TCU’s Payroll Oversight in Brazil. Inter-American Development Bank, November 2022. http://dx.doi.org/10.18235/0004549.

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This technical note documents the Continuous Payroll Audit Initiative within Brazils Court of Accounts (Tribunal de Contas da Unio, or TCU), presents its lessons learned, and makes recommendations that could improve its results. This initiative uses digital tools such as data analytics to proactively identify and address incorrect and/or illicit payments in the federal civil service and pension payroll. As of 2021, the initiative had led to savings close to $R 2 billion (US$515 million). The study demonstrates that a small team using the right technology can be very effective in rooting out irregularities in a complex system. However, technological innovation is not sufficient to address these issues. Broader systemic reforms in information collection and compliance are required for the system to fully achieve its goals. Given these results, this case could serve as reference for other supreme audit institutions around the world that are seeking to combat fraud and corruption.
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Feierl, Lukas, and Peter Luidolt. Automated monitoring, failure detection of key components, control strategies and self-learning controls of key components. IEA SHC Task 55, September 2020. http://dx.doi.org/10.18777/ieashc-task55-2020-0005.

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Bhakta, Tuhin, Jarle Haukås, Rolf Johan Lorentzen, Xiaodong Luo, and Geir Nævdal. Workflow for adding 4D seismic data in history matching. University of Stavanger, November 2021. http://dx.doi.org/10.31265/usps.204.

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In this document we present a workflow for ensemble-based 4D seismic history matching. Ensemble-based history matching has become standard for production data, but 4D seismic data poses a number of additional challenges. One issue is that the amount of data is considerably larger, but another, probably more complicating factor is that for utilizing the seismic data, either the seismic data must be inverted to properties that is included in the reservoir simulation model, or a seismic response must be modeled, given the current estimate of the reservoir properties. This leads to a number of choices on how to utilize the information of the 4D seismic data. We will discuss this, as well as point to approaches for handling large amounts of data in ensemble-based history matching. The developed approach has been applied on the Norne field and is currently being evaluated at the Ekofisk field. This document is primarily addressed to reservoir engineers and researchers that are working on history matching 4D seismic data, but it might also be of interest to those working with 4D seismic data from a geophysical perspective. After all, 4D seismic history matching should be viewed as an interdisciplinary subject. Although, our focus has been on ensemble-based history matching, some of the choices that have to be made in utilizing 4D seismic data is independent of the actual method used for history matching.
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Buathong, Thananon, Anna Dimitrova, Paolo Miguel M. Vicerra, and Montakarn Chimmamee. Years of Good Life: An illustration of a new well-being indicator using data for Thailand. Verlag der Österreichischen Akademie der Wissenschaften, August 2021. http://dx.doi.org/10.1553/populationyearbook2021.dat.1.

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While Thailand has achieved high levels of economic growth in recent decades, poverty at the local level has been increasing. Indicators of human development at the national level often mask the differences in well-being across communities. When responding to the need for sustainable development research, the heterogeneity of a population should be emphasised to ensure that no one is left behind. The Years of Good Life (YoGL) is a well-being indicator that demonstrates the similarities and differences between subpopulations in a given sociocultural context over time. The data used in this analysis were collected from Chiang Rai and Kalasin, which are provinces located in regions of Thailand with high poverty rates. Our main results indicate that the remaining years of good life (free from physical and cognitive limitations, out of poverty and satisfied with life) at age 20 among the sample population were 26 years for women and 28 years for men. The results varied depending on the indicators applied in each dimension of YoGL. Our analysis of the YoGL constituents indicated that cognitive functioning was the dimension that decreased the years of good life the most in the main specification. This study demonstrates the applicability of the YoGL methodology in investigating the wellbeing of subpopulations.
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Hinrichs, Peter L. State Appropriations and Employment at Higher Education Institutions. Federal Reserve Bank of Cleveland, November 2022. http://dx.doi.org/10.26509/frbc-wp-202232.

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This paper studies the impacts of state appropriations on staffing and salaries at public higher education institutions in the United States using employment and revenue data from the Integrated Postsecondary Education Data System, along with an instrumental variables strategy borrowed from Deming and Walters (2018) and Chakrabarti, Gorton, and Lovenheim (2020). The instrument sidesteps the potential endogeneity of state appropriations for a given institution in a given year by interacting an institution’s historical reliance on state appropriations with total state appropriations for all higher education institutions in a given year. The results suggest that higher state appropriations are associated with an increase in tenure-track assistant professors at four-year institutions. They are also associated with an increase in part-time instructional staff at both four-year and two-year institutions. However, they are not associated with a change in the number of tenured faculty. Appropriations are also positively related to salaries for a variety of employee groups, although notably not for instructional staff who are instructors, lecturers, or without an academic rank. Overall, the results show that public higher education institutions use state appropriations in a variety of ways, but I do not find evidence that they replace contingent faculty with tenured or tenure-track faculty when appropriations rise.
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VandenBerg, R. D., P. B. Kabanov, K E Dewing, and E. A. Atkinson. Geological and geochemical data from the Canadian Arctic Islands, part XVIII: XRF and TOC data, and formation tops in exploration wells from the Devonian clastic wedge and underlying strata, Northwest Territories and Nunavut. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329642.

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This collection of data comprises new XRF data, TOC data, and a new table of formation tops for the lower portion of the Devonian clastic wedge (Weatherall, Cape de Bray and Blackley formations sensu Embry and Klovan, 1976) and the underlying basinal and carbonate-platform strata of variable Ordovician to Lower-Middle Devonian age. Main results include ED-XRF data for 15 well sections within the N.W.T. jurisdiction of the SW Arctic Archipelago. These XRF data were obtained in 2018- 2020 through non-destructive measurements of drillhole cutting samples using a Bruker Tracer IV instrument. Testing of these samples has been restricted to preserve them for future study as they are irreplaceable. The goal of using the non destructives XFR has given us a methodology that does not harm these samples. We find this to be a reasonable method when data is required but no destructive testing is permitted, such as in these legacy wells. Reading acquisition procedure and instrument calibrations are discussed herein. These XRF logs cover cumulatively 12,538 m of well sections, which is the best attainable physical coverage for these strata in the absence of representative cores. For each section surveyed with XRF, we provide graphical striplogs with geophysical logs, descriptive lithology, XRF elemental logs, biostratigraphic data, and, selectively, synthetic seismograms and TOC data. Scientific discussion based on these results is a subject of a separate paper-in-preparation, (Kabanov, P. 2020.)
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