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Littérature scientifique sur le sujet « Given data »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 19 juillet 2025

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Articles de revues sur le sujet "Given data"

Zadelaar, Jacqueline N., Joost A. Agelink van Rentergem, and Hilde M. Huizenga. "Univariate comparisons given aggregated normative data." Clinical Neuropsychologist 31, no. 6-7 (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 (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 (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 (2017): 67–74. http://dx.doi.org/10.5815/ijisa.2017.01.07.

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Fejzić, Hajrudin. "Numerical Integration of Functions Given by Data Points." Sarajevo Journal of Mathematics 4, no. 1 (2024): 31–38. http://dx.doi.org/10.5644/sjm.04.1.03.

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Mccloughan, Patrick, and Esmaiel Abounoori. "How to estimate market concentration given grouped data." Applied Economics 35, no. 8 (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 (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 (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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Thèses sur le sujet "Given data"

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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Livres sur le sujet "Given data"

Euclid, ed. Dedomena: Euclid's Data, or, The importance of being given. 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.n.], 1992.

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

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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. World Scientific, 1987.

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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). World Meteorological Organization, 2000.

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Munerman, Viktor, Vadim Borisov, and Aleksandra Kononova. Mass data processing. Algebraic models and methods. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1906037.

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The monograph is devoted to mathematical and algorithmic support of mass data processing based on algebraic models. One of the most common classes of mass processing is considered - processing of highly active structured data. The construction of algebraic models of data and calculations and methods of proving their correspondence are analyzed. Three algebraic systems are studied, which can be used both as data models and as models of calculations. The algebraic and axiomatic methods of proving the correspondence of these models are investigated. A proof of their correspondence is given: homomorphism and isomorphism. The problem of optimizing the processes of mass processing of data presented in the form of algebraic expressions in the proposed algebra models is raised. The algorithms of synthesis and optimization of calculation of these expressions, the method of symmetric horizontal data distribution providing parallel implementation of calculation of algebraic expressions and generalization of the block algorithm of parallel matrix multiplication for the case of multiplication of multidimensional matrices are described in detail. Architectures of software and hardware complexes for effective parallel implementation of operations in the considered algebra models are proposed. A number of real-world examples illustrating the application of the proposed methods are given. For students, postgraduates and teachers of technical and physical-mathematical universities and faculties.

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Grigor'ev, Anatoliy, and Evgeniy Isaev. Methods and algorithms of data processing. 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. 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. 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. Magyar Tudományos Akadémia Nyelvtudományi Intézete, Institutum Linguisticum Academiae Scientiarum Hungaricae, 1991.

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Chapitres de livres sur le sujet "Given data"

Vapnik, Vladimir. "Estimation of Functional Values at Given Points." In Estimation of Dependences Based on Empirical Data. 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. CRC Press, 2021. http://dx.doi.org/10.1201/9780367814397-9.

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Blanchette, Jasmin, Qi Qiu, and Sophie Tourret. "Verified Given Clause Procedures." In Automated Deduction – CADE 29. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-38499-8_4.

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AbstractResolution and superposition provers rely on the given clause procedure to saturate clause sets. Using Isabelle/HOL, we formally verify four variants of the procedure: the well-known Otter and DISCOUNT loops as well as the newer iProver and Zipperposition loops. For each of the variants, we show that the procedure guarantees saturation, given a fair data structure to store the formulas that wait to be selected. Our formalization of the Zipperposition loop clarifies some fine points previously misunderstood in the literature.

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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. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5619-7_22.

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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. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/bfb0085483.

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Lasithan, L. G., P. V. Shouri, and V. G. Rajesh. "Defining Vibration Limits for Given Improvements in System Availability." In Advances in Data-driven Computing and Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0981-0_45.

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Bartkowiak, Anna, and Krystyna Ziętak. "Backprojection of data vectors using a given covariance matrix." In Advanced Computer Systems. 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. 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. 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. 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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Actes de conférences sur le sujet "Given data"

Ochiai, Yuki, Triet Nguyen-Van, and Shin Kawai. "Given Data of System Requirements for Canonical Controller Design." In 2025 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2025. https://doi.org/10.1109/sii59315.2025.10871107.

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Fernández, Manuel F., and Kai-Bor Yu. "An Improved Total Least Squares-Based Monopulse Ratio Estimate Given Multiple Data-Snapshots from a Uniform Line Array." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10993999.

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Helliwell, I. S., M. A. Turega, and R. A. Cottis. "Neural Networks for Corrosion Data Reduction." In CORROSION 1996. NACE International, 1996. https://doi.org/10.5006/c1996-96379.

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Abstract Artificial Neural Networks are being used increasingly in many fields of industry and commerce. Their ability to “learn by example” and to generalise this knowledge so as to give correct predictions to previously unseen data make them extremely attractive. There is great potential for applying this technology to corrosion problems as, in principle, artificial neural networks can ‘learn’ the behaviour of materials in a range of corrosive environments and thereby predict their behaviour. In practice, data in the literature is derived from differing sources, it is often of poor quality and important parameters are sometimes omitted. Also, care has to be exercised when applying artificial neural networks to ensure that their operational range is bounded and that some measure of output “quality” is given to the user. This paper will discuss the particular problems and limitations of applying neural networks to corrosion data and suggest ways in which these limitations can be overcome.

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Wang, Hongbin, and Srdjan Nešić. "CO2 Corrosion Model Verification Using Field Data." In CORROSION 2006. NACE International, 2006. https://doi.org/10.5006/c2006-06567.

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Abstract An integrated multiphase flow and corrosion prediction package was tested by comparing it’s performance with data obtained from the field. The comparisons indicated a satisfactory performance, even for the situations where incomplete information was available about the field cases. The results have shown that the effect of traces of H2S on CO2 corrosion needs to be given particular care when making simulations.

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Clark, Edward B. "CIS Data Enhanced by Soils Modeling." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07179.

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Abstract This paper uses field data from a variety of dig sites to evaluate whether soils data could be used in a model to predict locations where external corrosion would be an issue, as one approach to enhance the ECDA process. If by adding soils data to the previously collected ECDA datasets it could be shown that areas suffering corrosion could be predicted consistently, then operators would have an additional tool at their disposal to help maintain the country’s natural gas pipeline infrastructure safely and reliably. The approach targeted soils-corrosivity, because if corrosivity dominated a very simple model would be viable as a screening tool – with such a model then viable when other data is not available, unreliable, or difficult to obtain. Soil corrosivity was characterized in terms of a model that couples soils type with topography and drainage, with consideration also given to a simpler approach based on pH and resistivity. The results indicated that there is essentially no correlation between corrosion susceptibility based on soils-corrosivity expressed in terms of these two models. While an attempt was made to calibrate these measures of susceptibility using ILI data for corrosion incidence and severity, the frequency of corrosion for the sites evaluated was limited, which confounded this process. It follows that corrosivity alone cannot be viewed as the dominant factor controlling corrosion susceptibility. This absence of correlation is not surprising given the effectiveness of CP and coating integrity for the six sites used in this evaluation. The results indicate that if soils models are to be useful in guiding ECDA conducted in accordance with NACE Standard RP0502-2002 they must consider CP and coating integrity.

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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. International Association for Bridge and Structural Engineering (IABSE), 2020. http://dx.doi.org/10.2749/wroclaw.2020.1173.

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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.

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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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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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Rapports d'organisations sur le sujet "Given data"

Almås, Ingvild, Orazio Attanasio, Jyotsna Jalan, Francisco Oteiza, and Marcella Vigneri. Using data differently and using different data. Centre for Excellence and Development Impact and Learning (CEDIL), 2018. http://dx.doi.org/10.51744/cip8.

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The lack of adequate measures to capture relevant factors, and the prevalence of measurement error in existing ones, often constitute the main impediment to robust policy evaluation. Random assignment of a given treatment, when feasible, may allow for the identification of causal effects, given that the necessary measurements are available. Measurement challenges include: (a) adequately measuring outcomes of interest; (b) measuring factors that relate to the mechanisms of estimated impacts; and (c) conducting a robust evaluation in areas where the RCT methodology is not feasible. In this paper, we discuss three categories of related approaches to innovation in the use of data and measurements relevant for evaluation: the creation of new measures, the use of multiple measures, and the use of machine learning algorithms. We motivate the relevance of each of the categories by providing a series of detailed examples of cases where each approach has proved useful in impact evaluations. We discuss the challenges and risks involved in each strategy and conclude with an outline of promising directions for future work.

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Junghans, A., S. S. Westerdale, and P. Dimitriou. (alpha,n) Nuclear Data Evaluations and Data Needs. IAEA Nuclear Data Section, 2024. http://dx.doi.org/10.61092/iaea.d2d0-encd.

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The second IAEA Technical Meeting addressing (α,n) data needs for applications spanning reactor operation and safeguards, nonproliferation and spent fuel management, low-background experiments, and nuclear astrophysics was organized by the IAEA from 27 November to 1 December 2023. Fifty-six participants from thirteen Member States attended the virtual event. Participants reviewed the progress in (α,n) measurements, models, codes and evaluated libraries since the previous meeting of 2021. A summary of the presentations, technical discussions and recommendations is given in this report. The presentations are available from the meeting webpage: https://conferences.iaea.org/event/366/.

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Romero, Vicente, Clay Sanders, Timothy Walsh, and Cameron McCormick. Pragmatic Uncertainty Quantification and Propagation in Inverse Estimation of Structural Dynamics Parameters given Material Property Uncertainties and Limited Sensor Data. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2432203.

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Robertson, Rebecca, and Jonathan Wentworth. Understanding insect decline: data and drivers. Parliamentary Office of Science and Technology, 2020. http://dx.doi.org/10.58248/pb36.

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This POSTbrief provides further information on the data limitations for understanding insect declines and emerging methods to address these limitations. Further detail is also given on the evidence for drivers of insect declines, such as disease or artificial light at night, which are summarised in POSTnote 619. The POSTbrief also highlights areas where evidence is established or where there are gaps in knowledge, such as insect abundance 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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Westerdale, S. S., A. Junghans, R. J. deBoer, M. Pigni, and P. Dimitriou. Summary Report of the Technical Meeting on (alpha,n) Nuclear Data Evaluations and Data Needs. IAEA Nuclear Data Section, 2022. http://dx.doi.org/10.61092/iaea.vdj4-pakp.

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A Technical Meeting addressing (α,n) data needs for applications spanning reactor operation and safeguards, nonproliferation and spent fuel management, low-background experiments, and nuclear astrophysics was organised by the IAEA from 8 to 12 November 2021. Over 60 participants from fifteen Member States attended the virtual event. Participants reviewed the status of (α,n) measurements, models, codes and evaluated libraries with a view to identifying the gaps in the above areas and proposing the necessary actions to address them and produce reliable (α,n) data for the applications. A summary of the presentations, technical discussions and recommendations is given in this report. The presentations are available from the meeting webpage: https://conferences.iaea.org/event/283/.

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Engle, Jonathan W., Alan L. Nichols, and Roberto Capote Noy. Nuclear Data for Medical Applications. IAEA Nuclear Data Section, 2019. http://dx.doi.org/10.61092/iaea.6pjr-s8ta.

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A summary is given of a Technical Meeting on “Nuclear Data for Medical Applications” at which participants assessed future medical applications for many radionuclides based upon their existing and potential diagnostic and therapeutic properties. Debate focused upon charged-particle induced reactions and their production cross sections, derivation of optimal yields, minimisation of radionuclidic impurities, and nuclear data needs for proton and heavy-ion radiotherapy, along with outstanding decay data requirements. Technical discussions are included in this report, along with comprehensive listings and detailed recommendations for future work. Required cross-section measurements were identified for a reasonably wide range of targets and projectiles, along with decay data studies for specific radionuclides. Subsequent excitation functions and decay-data evaluations will also be needed to ensure the necessary quality and consistency of the datasets to be assembled in an existing dedicated IAEA-NDS database that merits regular maintenance and support.

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Farrigan, Tracey, and Austin Sanders. The Poverty Area Measures data product. Economic Research Service, U.S. Department of Agriculture, 2024. https://doi.org/10.32747/2024.8754225.ers.

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The U.S. Department of Agriculture's Poverty Area Measures (PAM) data product is designed to improve understanding of the geography of poverty in the United States. This report contains historical and technical documentation from the November 2022 version of PAM. Examples provided in this report are from 1960 through 2019, but the lessons will be applicable to PAM data in the future. PAM includes four measures of poverty: high, extreme, persistent, and the newly developed measure of enduring poverty. The methodology for the 2022 version of PAM incorporates reliability metrics to account for margin of error of the underlying data. The methodology also uniquely includes comparable U.S. county and census tract-level geography for all measures and data years (except for census tracts in 1960, given limited tract geography prior to 1970)

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Kibedi, Tibor, and Paraskevi Dimitriou. Improvement of Analysis Codes for Nuclear Structure and Decay Data Evaluations. IAEA Nuclear Data Section, 2019. http://dx.doi.org/10.61092/iaea.y4be-1t6s.

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A summary is given of a Technical Meeting assembled to review the progress in improving and developing new analysis and utility codes used in the evaluation of nuclear structure and decay data for the Evaluated Nuclear Structure Data File (ENSDF). Participants reviewed the existing and newly developed codes and discussed outstanding issues such as the consistent treatment of uncertainties, extending the ENSDF format to accommodate continuous data, updating the ENSDF manual and maintaining user-friendly online webtools and editors. Details of the discussions and the proposed actions are presented in this summary report.

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Otuka, Naohiko, and Boris Pritychenko. Summary Report of the Workshop on Compilation of Experimental Nuclear Reaction Data. IAEA Nuclear Data Section, 2023. http://dx.doi.org/10.61092/iaea.y5pd-w24h.

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This report summarizes the IAEA Workshop on Compilation of Experimental Nuclear Reaction Data held at the IAEA Headquarters in Vienna, Austria from 13 to 16 December 2022. The meeting was attended by 23 participants representing 12 cooperative Centres from seven Member States (China, Hungary, Japan, Korea, Russia, Ukraine and USA) and two International Organisations (NEA, IAEA) as well as a participant from Mongolia and Spain. A summary of the workshop is given in this report along with the conclusions and actions.

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