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Suche nach „[Hable] [Robert]“ hat 42 Publikationen gefunden
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    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Maschinelles Lernen erfolgreich nutzen

    DigiCamp zum Thema "4.0 braucht Künstliche Intelligenz (KI) - Praktische KI erleben", Deggendorf

    2019

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Fitting Additive Models With Regularized Kernel Methods: Methodology, Robustness Properties, and Business Applications

    DAGStat Conference 2019, München

    2019

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Statistische Daten in der Praxis: Zeitverschwendung oder Goldgrube?

    2018

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    BIG DATA in der Großküche - Was steckt dahinter, wo liegen die Chancen und Risiken?

    Jahresmitgliederversammlung des HKI Industrieverbands, Berlin

    2018

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    What Machine Learning Can Do

    TechDays, München

    2018

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Big Data in der Produktion

    2018

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Big Data - erste Schritte wagen! Praxisbeispiele und Handlungsempfehlungen für Unternehmen

    Sensorik Symposium, Regensburg

    2017

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Prognosen in Unternehmen: Praxisbeispiele und Handlungsempfehlungen

    Prognosekonferenz, Grafenau

    2017

    DigitalAngewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Big Data Analytics im Unternehmen: Strategien, Praxisbeispiele und Methoden

    Advanced Analytics Infrastructure Dialog, Frankfurt am Main

    2017

    TC Grafenau

    Zeitschriftenartikel

    C. Dupke, C. Bonenfant, M. Ewald, M. Heurich, Robert Hable, B. Reineking, T. Zeppenfeld

    Habitat selection by a large herbivore at multiple spatial and temporal scales is primarily governed by food resources

    Ecography - Pattern and Process in Ecology, vol. 40, no. 8, pp. 1014-1027

    2017

    Abstract anzeigen

    Habitat selection can be considered as a hierarchical process in which animals satisfy their habitat requirements at different ecological scales. Theory predicts that spatial and temporal scales should co‐vary in most ecological processes and that the most limiting factors should drive habitat selection at coarse ecological scales, but be less influential at finer scales. Using detailed location data on roe deer Capreolus capreolus inhabiting the Bavarian Forest National Park, Germany, we investigated habitat selection at several spatial and temporal scales. We tested 1) whether time‐varying patterns were governed by factors reported as having the largest effects on fitness, 2) whether the trade‐off between forage and predation risks differed among spatial and temporal scales and 3) if spatial and temporal scales are positively associated. We analysed the variation in habitat selection within the landscape and within home ranges at monthly intervals, with respect to land‐cover type and proxys of food and cover over seasonal and diurnal temporal scales. The fine‐scale temporal variation follows a nycthemeral cycle linked to diurnal variation in human disturbance. The large‐scale variation matches seasonal plant phenology, suggesting food resources being a greater limiting factor than lynx predation risk. The trade‐off between selection for food and cover was similar on seasonal and diurnal scale. Habitat selection at the different scales may be the consequence of the temporal variation and predictability of the limiting factors as much as its association with fitness. The landscape of fear might have less importance at the studied scale of habitat selection than generally accepted because of the predator hunting strategy. Finally, seasonal variation in habitat selection was similar at the large and small spatial scales, which may arise because of the marked philopatry of roe deer. The difference is supposed to be greater for wider ranging herbivores.

    DigitalInstitut ProtectITTC Grafenau

    Zeitschriftenartikel

    Karl Leidl, Robert Hable, Michael Fernandes, Nari Arunraj, Michael Heigl

    Comparison of Supervised, Semi-supervised and Unsupervised Learning Methods in Network Intrusion Detection Systems (NIDS) Application

    Anwendungen und Konzepte in der Wirtschaftsinformatik (AKWI), no. 6, pp. 10-19

    2017

    Abstract anzeigen

    With the emergence of the fourth industrial revolution (Industrie 4.0) of cyber physical systems, intrusion detection systems are highly necessary to detect industrial network attacks. Recently, the increase in application of specialized machine learning techniques is gaining critical attention in the intrusion detection community. A wide variety of learning techniques proposed for different network intrusion detection system (NIDS) problems can be roughly classified into three broad categories: supervised, semi-supervised and unsupervised. In this paper, a comparative study of selected learning methods from each of these three kinds is carried out. In order to assess these learning methods, they are subjected to investigate network traffic datasets from an Airplane Cabin Demonstrator. In addition to this, the imbalanced classes (normal and anomaly classes) that are present in the captured network traffic data is one of the most crucial issues to be taken into consideration. From this investigation, it has been identified that supervised learning methods (logistic and lasso logistic regression methods) perform better than other methodswhen historical data on former attacks are available. The results of this study have also showed that the performance of semi-supervised learning method (One class support vector machine) is comparatively better than unsupervised learning method (Isolation Forest) when historical data on former attacks are not available.

    DigitalGesundAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    J. Riemann, G. Tontini, M. Neurath, H. Albrecht, H. Neumann, M. Vieth, Robert Hable, J. Gallitz

    The Offer of Advanced Imaging Techniques Leads to Higher Acceptance Rates for Screening Colonoscopy - A Prospective Multivariate Analysis of Data From a Patient Questionnaire

    Gastrointestinal Endoscopy, vol. 83, no. 5

    2016

    DOI: 10.1016/j.gie.2016.03.916

    GesundAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    J. Riemann, G. Tontini, M. Neurath, H. Albrecht, H. Neumann, M. Vieth, Robert Hable, J. Gallitz

    The Offer of Advanced Imaging Techniques Leads to Higher Acceptance Rates for Screening Colonoscopy - a Prospective Study

    Asian Pacific Journal of Cancer Prevention, vol. 17, no. 8, pp. 3871-3875

    2016

    Abstract anzeigen

    Colonoscopy plays a fundamental role in early diagnosis and management of colorectal cancer and requires public and professional acceptance to ensure the ongoing success of screening programs. The aim of the study was to prospectively assess whether patient acceptance rates to undergo screening colonoscopy could be improved by the offer of advanced imaging techniques. Materials and Methods Overall, 372 randomly selected patients were prospectively included. A standardized questionnaire was developed that inquired of the patients their knowledge regarding advanced imaging techniques. Second, several media campaigns and information events were organized reporting about advanced imaging techniques, followed by repeated evaluation. After one year the evaluation ended. Results At baseline, 64% of the patients declared that they had no knowledge about new endoscopic methods. After twelve months the overall grade of information increased signi cantly from 14% at baseline to 34%. The percentage of patients who decided to undergo colonoscopy because of the offer of new imaging methods also increased signi cantly from 12% at baseline to 42% after 12 months. Conclusions Patients were highly interested in the offer of advanced imaging techniques. Knowledge about these techniques could relatively easy be provided using local media campaigns. The offer of advanced imaging techniques leads to higher acceptance rates for screening colonoscopies.

    NachhaltigAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    K. Müller, B. Huwe, Robert Hable, O. Fishkis

    Effects of Throughfall Exclusion, Soil Texture and Spatial Continuity on Soil Water Repellency in Fichtel Mountains

    Soil Science Society of America Journal, vol. 80, pp. 554-562

    2016

    DOI: 10.2136/sssaj2015.10.0386

    Abstract anzeigen

    The occurrence of soil water repellency (SWR) in soil is controlled by soil organic matter (SOM) composition and is strongly soil-moisture dependent. During drying the reduction of water content in soil has been shown to induce the outward orientation of nonpolar ends of organic compounds and hence the increase in SWR. A prolonged drought can however also induce changes in SOM composition which in turn can affect SWR. In this study, we eliminate differences in water content after prolonged throughfall exclusion and a control treatment by oven-drying of the soil samples, to test if a prolonged drought affects SWR even after excluding the direct effect of soil moisture. In addition, the relevance of soil texture variability and spatial dependence of SWR for prediction of soil wettability distribution over the study area was explored. The samples of the upper mineral soil horizon were taken from six plots in Fichtel Mountains, subjected to a throughfall exclusion or control treatments, oven-dried and analyzed for soil texture and water drop penetration time (WDPT). A linear model with spatially correlated random effects was used to quantify the effects of soil texture and treatment on the persistence of the SWR and to simultaneously evaluate the spatial structure of the SWR. Based on estimated parameters the persistence of SWR was calculated on unsampled locations by robust kriging with external drift. The throughfall exclusion treatment significantly increased the log(WDPT) (p < 0.01) of the oven-dried soil by 0.46. The clay content and the sand content had highly significant (p < 0.001) negative effects, while silt content had positive effects on the log(WDPT). The variogram parameter with a range of 5.2 m, a nugget of 0.25, and a sill of 0.45 indicated a rather low degree of spatial dependence of log(WDPT). The main outcome of this study is that the positive effect of throughfall exclusion on SWR cannot be fully attributed to water content reduction. Most probably the drought-induced changes in SOM composition and microbial community were responsible for the observed increase in SWR.

    DigitalAngewandte InformatikTC Grafenau

    Zeitschriftenartikel

    K. Strohriegel, Robert Hable

    Qualitative robustness of estimators on stochastic processes

    Metrika, vol. 79, no. 8, pp. 895-917

    2016

    DOI: 10.1007/s00184-016-0582-z

    Abstract anzeigen

    A lot of statistical methods originally designed for independent and identically distributed (i.i.d.) data are also successfully used for dependent observations. Still most theoretical investigations on robustness assume i.i.d. pairs of random variables. We examine an important property of statistical estimators—the qualitative robustness in the case of observations which do not fulfill the i.i.d. assumption. In the i.i.d. case qualitative robustness of a sequence of estimators is, according to Hampel (Ann Math Stat 42:1887–1896, 1971), ensured by continuity of the corresponding statistical functional. A similar result for the non-i.i.d. case is shown in this article. Continuity of the corresponding statistical functional still ensures qualitative robustness of the estimator as long as the data generating process satisfies a certain convergence condition on its empirical measure. Examples for processes providing such a convergence condition, including certain Markov chains or mixing processes, are given as well as examples for qualitatively robust estimators in the non-i.i.d. case.

    Angewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Statistical Properties of Support Vector Machines and Related Methods from Machine Learning: Theory and Applications

    1. Bayerisch-Tschechische Wissenschaftskonferenz "Datenanalyse", Jindřichův Hradec, Tschechische Republik

    2015

    Angewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Maschinelles Lernen: Datenanalyse mit Methoden der künstlichen Intelligenz

    Gastvortrag in Vorlesung zu "Big Data-Algorithms and Systems"

    2015

    Angewandte InformatikTC Grafenau

    Vortrag

    Robert Hable

    Nichtparametrische Klassifikation und Regression mit maschinellen Lernverfahren: Theorie und Anwendungen

    2015

    TC Grafenau

    Buch (Monographie)

    Robert Hable

    Einführung in die Stochastik

    Ein Begleitbuch zur Vorlesung

    SpringerSpektrum Lehrbuch, Berlin [u.a.]

    2015

    ISBN: 978-3-662-43497-0

    TC Grafenau

    Zeitschriftenartikel

    M. Wachten, Robert Hable, O. Fishkis

    Assessment of soil water repellency as a function of soil moisture with mixed modelling

    European Journal of Soil Science, vol. 66, no. 5, pp. 910-920

    2015

    DOI: 10.1111/ejss.12283

    Abstract anzeigen

    An understanding of the relation between soil water repellency (SWR) and soil moisture is a prerequisite of water-flow modelling in water-repellent soil. Here, the relation between SWR and soil moisture was investigated with intact cores of soil taken from three types of soil with different particle-size distributions. The SWR was measured by a sessile drop contact angle (CA) during drying at soil pF values that ranged from −∞ to 4.2. From the measured CA, the work of adhesion (Wa) was calculated and its relation with the pF-value was explored. Mixed modelling was applied to evaluate the effects of pF, soil type and soil depth on CA and Wa. For all soil types, a positive relation was observed between CA and the pF-value that could be represented by a linear model for the pF-range of 1–4.2. The variation in slope and intercept of the CA–pF relationship caused by heterogeneity of the samples taken from a single soil horizon was quantified. In addition, the relation between CA and water content (WC) showed hysteresis, with significantly larger CAs during drying than during wetting.