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  1. Visualizing probability distributions across bivariate cyclic temporal granularities
    Autor*in: Gupta, Sayani; Hyndman, Rob J.; Cook, Dianne; Unwin, Antony
    Erschienen: September 2020
    Verlag:  Monash University, Department of Econometrics and Business Statistics, [Victoria, Australia]

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    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; 20, 35
    Schlagworte: data visualization; statistical distributions; time granularities; calendar algebra; periodicities; grammar of graphics; R
    Umfang: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  2. Detecting distributional differences between temporal granularities for exploratory time series analysis
    Autor*in: Gupta, Sayani; Hyndman, Rob J.; Cook, Dianne
    Erschienen: November 2021
    Verlag:  Monash University, Department of Econometrics and Business Statistics, [Victoria, Australia]

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    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; 21, 20
    Schlagworte: data visualization; cyclic granularities; periodicities; permutation tests; distributional difference; Jensen-Shannon distances; smart meter data; R
    Umfang: 1 Online-Ressource (circa 25 Seiten), Illustrationen
  3. Sentiment and econometrics
    toward a unified framework of textual sentiment analysis for economic and financial applications
    Autor*in: Borms, Samuel
    Erschienen: July 2020

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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Dissertation
    Format: Online
    Schlagworte: Aggregation; Econometrics; EPU; ESG; Penalized Regression; Qualitative Data; R; Sentiment Analysis; Sentometrics; sentometrics; Sustainable Investment; Textual Analysis; Time Series
    Umfang: 1 Online-Ressource (circa 176 Seiten), Illustrationen
    Bemerkung(en):

    Enthält 4 Beiträge

    Dissertation, Université de Neuchâtel, 2020

    Dissertation, Vrije Universiteit Brussel, 2020
  4. Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016
    Autor*in: Forbes, Jeremy; Cook, Dianne; Hyndman, Rob J.
    Erschienen: May 2019
    Verlag:  Monash University, Department of Econometrics and Business Statistics, [Victoria, Australia]

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    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; 19, 08
    Schlagworte: federal election; Census; Australia; spatial modelling; imputation; data science; socio-demographics; electorates; R; eechidna
    Umfang: 1 Online-Ressource (circa 23 Seiten), Illustrationen
  5. Calendar-based graphics for visualizing people's daily schedules
    Autor*in: Wang, Earo; Cook, Dianne; Hyndman, Rob J.
    Erschienen: May 2019
    Verlag:  Monash University, Department of Econometrics and Business Statistics, [Victoria, Australia]

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    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; 19, 11
    Schlagworte: data visualization; statistical graphics; time series; grammar of graphics; R
    Umfang: 1 Online-Ressource (circa 26 Seiten), Illustrationen
  6. A new tidy data structure to support exploration and modeling of temporal data
    Autor*in: Wang, Earo; Cook, Dianne; Hyndman, Rob J.
    Erschienen: May 2019
    Verlag:  Monash University, Department of Econometrics and Business Statistics, [Victoria, Australia]

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    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Working paper / Monash University, Department of Econometrics and Business Statistics ; 19, 12
    Schlagworte: time series; data wrangling; tidy data; R; forecasting; data science; exploratory data analysis; data pipelines
    Umfang: 1 Online-Ressource (circa 29 Seiten), Illustrationen
  7. Inherited dollarization: persistence of US Dollar pricing in consumer goods markets
    Autor*in: Landaberry, Victoria; Mello Costa, Miguel
    Erschienen: [2019]
    Verlag:  [Banco Central del Uruguay], [Montevideo, Uruguay]

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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Documento de trabajo / Banco Central del Uruguay ; no 2019, 005
    Schlagworte: Price setting; foreign currency; dollarization; Uruguay; web scraping; persistence; R; data analysis
    Umfang: 1 Online-Ressource (circa 28 Seiten), Illustrationen
  8. Stochastic frontier analysis for healthcare, with illustrations in R
    Autor*in: Sickles, Robin C.; Wang, Zhichao; Zelenyuk, Valentin
    Erschienen: May 2022
    Verlag:  School of Economics, University of Queensland, St. Lucia, Qld., Australia

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    Schriftenreihe: Working paper series / Centre for Efficiency and Productivity Analysis ; 2022, no. WP 05
    Schlagworte: Stochastic frontier analysis; R; healthcare; hospital; Queensland
    Umfang: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  9. Efficiency analysis with stochastic frontier models using popular statistical softwares
    Autor*in: Bao Hoang Nguyen; Sickles, Robin C.; Zelenyuk, Valentin
    Erschienen: June 2021
    Verlag:  School of Economics, University of Queensland, St. Lucia, Qld., Australia

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    Schriftenreihe: Working paper series / Centre for Efficiency and Productivity Analysis ; 2021, no. WP 09
    Schlagworte: Technical efficiency; Stochastic frontier analysis; Panel data; Semi-parametric,Stata; Matlab; R
    Umfang: 1 Online-Ressource (circa 45 Seiten), Illustrationen
  10. Performance of long short-term memory artificial neural networks in nowcasting during the COVID-19 crisis
    Autor*in: Hopp, Daniel
    Erschienen: November 2021
    Verlag:  United Nations, Geneva

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    Schriftenreihe: UNCTAD research paper ; No. 74
    Schlagworte: Nowcasting; Economic forecast; Neural networks; Machinelearning; Python; R; MATLAB; Julia; LSTM; COVID
    Umfang: 1 Online-Ressource (circa 24 Seiten), Illustrationen
  11. Clustering the Swiss Pension Register
    Autor*in: Lettry, Layal Christine
    Erschienen: February 27, 2023
    Verlag:  University of Fribourg, Switzerland, Faculty of Management, Economics and Social Sciences, Fribourg

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    Beteiligt: Donzé, Laurent (MitwirkendeR)
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Working papers SES / Université de Fribourg, Faculté des sciences économiques et sociales et du management ; n. 529 (II. 2023)
    Schlagworte: Kamila; Clustering; R; AVS; AHV; OASI; Swiss Pension Register; FSIO; prediction strength criterion; classification; RAMD; AADR; UniFr
    Umfang: 1 Online-Ressource (circa 132 Seiten), Illustrationen
  12. Humanities data in R
    exploring networks, geospatial data, images, and text
    Autor*in: Arnold, Taylor; Tilton, Lauren
    Erschienen: 2015
    Verlag:  Springer, Cham [u.a.]

    Standort:
    Universitäts- und Landesbibliothek Bonn
    Signatur:
    2018/6870
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    Universitätsbibliothek Dortmund
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    Sprache: Englisch
    Medientyp: Buch (Monographie)
    ISBN: 9783319207018; 9783319207025
    RVK Klassifikation: ST 250
    Schriftenreihe: Quantitative methods in the humanities and social sciences
    Schlagworte: Quantitative Bildanalyse; Netzwerkanalyse <Soziologie>; Sprachanalyse; Raumdaten; R <Programm>; Digital Humanities
    Umfang: XIII, 211 S., Ill., graph. Darst.
  13. Text analysis with R
    for students of literature
    Autor*in: Jockers, Matthew Lee; Thalken, Rosamond
    Erschienen: [2020]
    Verlag:  Springer, Cham

    Standort:
    Freie Universität Berlin, Universitätsbibliothek
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    Standort:
    Hochschule für Technik und Wirtschaft Berlin, Hochschulbibliothek
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    Brandenburgische Technische Universität Cottbus - Senftenberg, Universitätsbibliothek
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    Hinweise zum Inhalt
    Volltext (URL des Erstveröffentlichers)
    Quelle: Philologische Bibliothek, FU Berlin
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9783030396435
    Weitere Identifier:
    RVK Klassifikation: EC 1300 ; ES 275 ; ES 940 ; ST 250 ; ST 680
    Auflage/Ausgabe: Second edition
    Schriftenreihe: Quantitative methods in the humanities and social sciences
    Schlagworte: Statistics and Computing/Statistics Programs; Computational Linguistics; Statistics for Social Sciences, Humanities, Law; Digital Humanities; Literature and Technology/Media; Computer Appl. in Arts and Humanities; Statistics ; Computational linguistics; Humanities—Digital libraries; Technology in literature; Application software; R <Programm>; Textanalyse
    Umfang: 1 Online-Ressource (xxiii, 277 Seiten), Illustrationen
  14. Text analysis with R
    for students of literature
    Autor*in: Jockers, Matthew Lee; Thalken, Rosamond
    Erschienen: [2020]; © 2020
    Verlag:  Springer, Cham, Switzerland

    Standort:
    Humboldt-Universität zu Berlin, Universitätsbibliothek, Jacob-und-Wilhelm-Grimm-Zentrum
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    ISBN: 9783030396428; 9783030396442; 9783030396459
    RVK Klassifikation: EC 1300 ; ST 250 ; ST 680 ; ES 275 ; ES 940
    Auflage/Ausgabe: Second edition
    Schriftenreihe: Quantitative methods in the humanities and social sciences
    Schlagworte: Statistics and Computing/Statistics Programs; Computational Linguistics; Statistics for Social Sciences, Humanities, Law; Digital Humanities; Literature and Technology/Media; Computer Appl. in Arts and Humanities; Statistics ; Computational linguistics; Humanities—Digital libraries; Technology in literature; Application software; R <Programm>; Textanalyse
    Umfang: xxiii, 277 Seiten, Illustrationen, Diagramme
  15. Target discovery screens using pooled shRNA libraries and next-generation sequencing: A model workflow and analytical algorithm.
    Autor*in: Christiane Schaefer; Nikhil Mallela; Jochen Seggewiß; Birgit Lechtape; Heymut Omran; Uta Dirksen; Eberhard Korsching; Jenny Potratz
    Erschienen: 2018
    Verlag:  Public Library of Science (PLoS)

    In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing... mehr

     

    In the search for novel therapeutic targets, RNA interference screening has become a valuable tool. High-throughput technologies are now broadly accessible but their assay development from baseline remains resource-intensive and challenging. Focusing on this assay development process, we here describe a target discovery screen using pooled shRNA libraries and next-generation sequencing (NGS) deconvolution in a cell line model of Ewing sarcoma. In a strategy designed for comparative and synthetic lethal studies, we screened for targets specific to the A673 Ewing sarcoma cell line. Methods, results and pitfalls are described for the entire multi-step screening procedure, from lentiviral shRNA delivery to bioinformatics analysis, illustrating a complete model workflow. We demonstrate that successful studies are feasible from the first assay performance and independent of specialized screening units. Furthermore, we show that a resource-saving screen depth of 100-fold average shRNA representation can suffice to generate reproducible target hits despite heterogeneity in the derived datasets. Because statistical analysis methods are debatable for such datasets, we created ProFED, an analysis package designed to facilitate descriptive data analysis and hit calling using an aim-oriented profile filtering approach. In its versatile design, this open-source online tool provides fast and easy analysis of shRNA and other count-based datasets to complement other analytical algorithms.

     
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    Sprache: Englisch
    Medientyp: Aufsatz aus einer Zeitschrift
    Format: Online
    Übergeordneter Titel: PLoS ONE, Vol 13, Iss 1, p e0191570 (2018)
    Schlagworte: Medicine; R; Science; Q
  16. Ontology-based data integration between clinical and research systems.
    Autor*in: Sebastian Mate; Felix Köpcke; Dennis Toddenroth; Marcus Martin; Hans-Ulrich Prokosch; Thomas Bürkle; Thomas Ganslandt
    Erschienen: 2015
    Verlag:  Public Library of Science (PLoS)

    Data from the electronic medical record comprise numerous structured but uncoded elements, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the... mehr

     

    Data from the electronic medical record comprise numerous structured but uncoded elements, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of relevant data elements and the creation of database jobs for extraction, transformation and loading (ETL) are challenging: With current methods such as data warehousing, it is not feasible to efficiently maintain and reuse semantically complex data extraction and trans-formation routines. We present an ontology-supported approach to overcome this challenge by making use of abstraction: Instead of defining ETL procedures at the database level, we use ontologies to organize and describe the medical concepts of both the source system and the target system. Instead of using unique, specifically developed SQL statements or ETL jobs, we define declarative transformation rules within ontologies and illustrate how these constructs can then be used to automatically generate SQL code to perform the desired ETL procedures. This demonstrates how a suitable level of abstraction may not only aid the interpretation of clinical data, but can also foster the reutilization of methods for un-locking it.

     
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    Übergeordneter Titel: PLoS ONE, Vol 10, Iss 1, p e0116656 (2015)
    Schlagworte: Medicine; R; Science; Q
  17. Low-order non-spatial effects dominate second-order spatial effects in the texture quantifier analysis of 18F-FDG-PET images.
    Autor*in: Frank J Brooks; Perry W Grigsby
    Erschienen: 2015
    Verlag:  Public Library of Science (PLoS)

    Background There is increasing interest in applying image texture quantifiers to assess the intra-tumor heterogeneity observed in FDG-PET images of various cancers. Use of these quantifiers as prognostic indicators of disease outcome and/or treatment... mehr

     

    Background There is increasing interest in applying image texture quantifiers to assess the intra-tumor heterogeneity observed in FDG-PET images of various cancers. Use of these quantifiers as prognostic indicators of disease outcome and/or treatment response has yielded inconsistent results. We study the general applicability of some well-established texture quantifiers to the image data unique to FDG-PET. Methods We first created computer-simulated test images with statistical properties consistent with clinical image data for cancers of the uterine cervix. We specifically isolated second-order statistical effects from low-order effects and analyzed the resulting variation in common texture quantifiers in response to contrived image variations. We then analyzed the quantifiers computed for FIGOIIb cervical cancers via receiver operating characteristic (ROC) curves and via contingency table analysis of detrended quantifier values. Results We found that image texture quantifiers depend strongly on low-effects such as tumor volume and SUV distribution. When low-order effects are controlled, the image texture quantifiers tested were not able to discern only the second-order effects. Furthermore, the results of clinical tumor heterogeneity studies might be tunable via choice of patient population analyzed. Conclusion Some image texture quantifiers are strongly affected by factors distinct from the second-order effects researchers ostensibly seek to assess via those quantifiers.

     
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    Übergeordneter Titel: PLoS ONE, Vol 10, Iss 2, p e0116574 (2015)
    Schlagworte: Medicine; R; Science; Q
  18. Prediction of oncogenic interactions and cancer-related signaling networks based on network topology.
    Autor*in: Marcio Luis Acencio; Luiz Augusto Bovolenta; Esther Camilo; Ney Lemke
    Erschienen: 2013
    Verlag:  Public Library of Science (PLoS)

    Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous... mehr

     

    Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI). This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved in cancer research interested in detecting signaling networks most ...

     
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    Übergeordneter Titel: PLoS ONE, Vol 8, Iss 10, p e77521 (2013)
    Schlagworte: Medicine; R; Science; Q
  19. Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis
    Autor*in: Hamidreza Dehghan Tazarjani; Zahra Amini; Rahele Kafieh; Fereshteh Ashtari; Erfan Sadeghi
    Erschienen: 2021
    Verlag:  Hindawi Limited

    Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current... mehr

     

    Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current diagnosis protocol for MS is MRI, but newer modalities like Optical Coherence Tomography (OCT) are already of interest in early detection and progression analysis. OCT reveals the symptoms of MS in the Central Nervous System (CNS) through cross-sectional images from neural retinal layers. Previous works on OCT were mostly focused on the thickness of retinal layers; however, texture features seem also to have information in this regard. In this research, we introduce a new pipeline that constructs layer-stacked (LS) images containing data from each specific layer. A variety of texture features are then extracted from LS images to differentiate between healthy controls and ON/None-ON MS cases. Furthermore, the definition of texture extraction methods is tailored for this application. After performing a vast survey on available texture analysis methods, a treasury of powerful features is collected in this paper. As a primary work, this paper shows the ability of such features in the diagnosis of HC and MS (ON and None-ON) cases. Our findings show that the texture features are powerful to diagnose MS cases. Furthermore, adding information of conventional thickness values to texture features improves considerably the discrimination between most of the target groups including HC vs. MS, HC vs. MS-None-ON, and HC vs. MS-ON.

     
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    Sprache: Englisch
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    Übergeordneter Titel: BioMed Research International, Vol 2021 (2021)
    Schlagworte: Medicine; R
  20. A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data
    Autor*in: Diana M. Pérez-Valencia; María Xosé Rodríguez-Álvarez; Martin P. Boer; Lukas Kronenberg; Andreas Hund; Llorenç Cabrera-Bosquet; Emilie J. Millet; Fred A. van Eeuwijk
    Erschienen: 2022
    Verlag:  Nature Portfolio

    Abstract High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which... mehr

     

    Abstract High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical analyses in which longitudinal genetic signals need to be estimated against a background of spatio-temporal noise processes. We propose a two-stage approach for the analysis of such longitudinal HTP data. In a first stage, we correct for design features and spatial trends per time point. In a second stage, we focus on the longitudinal modelling of the spatially corrected data, thereby taking advantage of shared longitudinal features between genotypes and plants within genotypes. We propose a flexible hierarchical three-level P-spline growth curve model, with plants/plots nested in genotypes, and genotypes nested in populations. For selection of genotypes in a plant breeding context, we show how to extract new phenotypes, like growth rates, from the estimated genotypic growth curves and their first-order derivatives. We illustrate our approach on HTP data from the PhenoArch greenhouse platform at INRAE Montpellier and the outdoor Field Phenotyping platform at ETH Zürich.

     
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    Übergeordneter Titel: Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
    Schlagworte: Medicine; R; Science; Q
  21. An efficient 3D column-only P300 speller paradigm utilizing few numbers of electrodes and flashings for practical BCI implementation.
    Autor*in: Onur Erdem Korkmaz; Onder Aydemir; Emin Argun Oral; Ibrahim Yucel Ozbek
    Erschienen: 2022
    Verlag:  Public Library of Science (PLoS)

    The event related P300 potentials, positive waveforms in electroencephalography (EEG) signals, are often utilized in brain computer interfaces (BCI). Many studies have been carried out to improve the performance of P300 speller systems either by... mehr

     

    The event related P300 potentials, positive waveforms in electroencephalography (EEG) signals, are often utilized in brain computer interfaces (BCI). Many studies have been carried out to improve the performance of P300 speller systems either by developing signal processing algorithms and classifiers with different architectures or by designing new paradigms. In this study, a new paradigm is proposed for this purpose. The proposed paradigm combines two remarkable properties of being a 3D animation and utilizing column-only flashings as opposed to classical paradigms which are based on row-column flashings in 2D manner. The new paradigm is utilized in a traditional two-layer artificial neural networks model with a single output neuron, and numerous experiments are conducted to evaluate and compare the performance of the proposed paradigm with that of the classical approach. The experimental results, including statistical significance tests, are presented for single and multiple EEG electrode usage combinations in 1, 3 and 15 flashing repetitions to detect P300 waves as well as to recognize target characters. Using the proposed paradigm, the best average classification accuracy rates on the test data are improved from 89.97% to 93.90% (an improvement of 4.36%) for 1 flashing, from 97.11% to 98.10% (an improvement of 1.01%) for 3 flashings and from 99.70% to 99.81% (an improvement of 0.11%) for 15 flashings when all electrodes, included in the study, are utilized. On the other hand, the accuracy rates are improved by 9.69% for 1 flashing, 4.72% for 3 flashings and 1.73% for 15 flashings when the proposed paradigm is utilized with a single EEG electrode (P8). It is observed that the proposed speller paradigm is especially useful in BCI systems designed for few EEG electrodes usage, and hence, it is more suitable for practical implementations. Moreover, all participants, given a subjective test, declared that the proposed paradigm is more user-friendly than classical ones.

     
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    Sprache: Englisch
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    Format: Online
    Übergeordneter Titel: PLoS ONE, Vol 17, Iss 4, p e0265904 (2022)
    Schlagworte: Medicine; R; Science; Q
  22. OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB.
    Autor*in: Lucian A B Purvis; William T Clarke; Luca Biasiolli; Ladislav Valkovič; Matthew D Robson; Christopher T Rodgers
    Erschienen: 2017
    Verlag:  Public Library of Science (PLoS)

    In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these... mehr

     

    In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from github.com/oxsatoolbox/oxsa.

     
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    Format: Online
    Übergeordneter Titel: PLoS ONE, Vol 12, Iss 9, p e0185356 (2017)
    Schlagworte: Medicine; R; Science; Q
  23. Episodic Reasoning for Vision-Based Human Action Recognition
    Autor*in: Maria J. Santofimia; Jesus Martinez-del-Rincon; Jean-Christophe Nebel
    Erschienen: 2014
    Verlag:  Hindawi Limited

    Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis... mehr

     

    Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

     
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    Sprache: Englisch
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    Format: Online
    Übergeordneter Titel: The Scientific World Journal, Vol 2014 (2014)
    Schlagworte: Technology; T; Medicine; R; Science; Q
  24. Humanities data in R
    exploring networks, geospatial data, images, and text
    Autor*in: Arnold, Taylor; Tilton, Lauren
    Erschienen: [2015]; © 2015
    Verlag:  Springer, Cham ; Heidelberg ; New York ; Dordrecht ; London

    "This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods,... mehr

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    Universitätsbibliothek Bamberg
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    Universitätsbibliothek Eichstätt-Ingolstadt
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    "This pioneering book teaches readers to use R within four core analytical areas applicable to the Humanities: networks, text, geospatial data, and images. This book is also designed to be a bridge: between quantitative and qualitative methods, individual and collaborative work, and the humanities and social scientists. Exploring Humanities Data Types with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis (continuous and categorical data, multivariate analysis, and advanced graphics with emphasis on aesthetics and facility). Everything is hands-on: networks are explained using U.S. Supreme Court opinions, and low-level NLP methods are applied to short stories by Sir Arthur Conan Doyle. The book?s data, code, appendix with 100 basic programming exercises and solutions, and dedicated website are valuable resources for readers. The methodology will have wide application in classrooms and self-study for the humanities, but also for use in linguistics, anthropology, and political science. Outside the classroom, this intersection of humanities and computing is particularly relevant for research and new modes of dissemination across archives, museums and libraries."--Page 4 de la couverture

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    ISBN: 9783319207018; 9783319366715
    RVK Klassifikation: ST 601 ; ST 250 ; ES 275 ; AK 39950
    Schriftenreihe: Quantitative methods in the humanities and social sciences
    Schlagworte: Raumdaten; Netzwerkanalyse <Soziologie>; Digital Humanities; Quantitative Bildanalyse; R <Programm>; Sprachanalyse
    Weitere Schlagworte: Statistique; Progiciels; Linguistique / Informatique; Sciences sociales; Humanities / Statistical methods / Data processing; Sciences humaines / Méthodes statistiques / Informatique; Mathematical statistics; Statistique mathématique; R (Computer program language); R (Langage de programmation); Mathematical statistics; R (Computer program language)
    Umfang: xiii, 211 Seiten, Illustrationen, Diagramme, Karten
    Bemerkung(en):

    Set-up -- A Short Introduction to R -- EDA I Continuous and Categorical Data -- EDA II Multivariate Analysis -- EDA III Advanced Graphics -- Networks -- Geospatial Data -- Image Data -- Natural Language Processing -- Text Analysis -- Appendix
  25. Humanities data in R
    exploring networks, geospatial data, images, and text
    Beteiligt: Arnold, Taylor (Hrsg.); Tilton, Lauren (Hrsg.)
    Erschienen: [2015]; © 2015
    Verlag:  Springer, Cham

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    Universitätsbibliothek Bayreuth
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    Technische Universität München, Universitätsbibliothek
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    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Beteiligt: Arnold, Taylor (Hrsg.); Tilton, Lauren (Hrsg.)
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9783319207025
    Weitere Identifier:
    RVK Klassifikation: ST 250 ; ST 601 ; AK 39950 ; ES 275
    Schriftenreihe: Quantitative methods in the humanities and social sciences
    Schlagworte: Statistics; Application software; Computational linguistics; Anthropology; Social sciences; Statistics and Computing/Statistics Programs; Computer Appl. in Arts and Humanities; Methodology of the Social Sciences; Computational Linguistics; Sozialwissenschaften; Statistik; Digital Humanities; Quantitative Bildanalyse; Raumdaten; Sprachanalyse; R <Programm>; Netzwerkanalyse <Soziologie>
    Umfang: 1 Online Ressource (XIII, 211 Seiten, 50 illus., 33 illus. in color)