GesundAngewandte InformatikTC Grafenau
H. Albrecht, J. Gallitz, Robert Hable, M. Vieth, G. Tontini, M. Neurath, J. Riemann, H. Neumann
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
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
O. Fishkis, K. Müller, Robert Hable, B. Huwe
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
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
K. Strohriegel, Robert Hable
Qualitative robustness of estimators on stochastic processes
Metrika, vol. 79, no. 8, pp. 895-917
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.
C. Dupke, C. Bonenfant, B. Reineking, Robert Hable, T. Zeppenfeld, M. Ewald, M. Heurich
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
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
Nari Arunraj, Robert Hable, Michael Fernandes, Karl Leidl, 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
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.
Angewandte InformatikTC Grafenau
Nichtparametrische Klassifikation und Regression mit SVMs und anderen regularisierten Kern-Verfahren: Statistische Modelle und Inferenz
Kolloquium des Instituts für Medizinische Biometrie und Statistik der Universität Lübeck, Lübeck
Angewandte InformatikTC Grafenau
Statistical Properties of Support Vector Machines and Related Methods from Machine Learning: Theory and Applications
1. Bayerisch-Tschechische Wissenschaftskonferenz "Datenanalyse", Jindřichův Hradec, Tschechische Republik
Beitrag (Sammelband oder Tagungsband)
Data-Based Decisions under Imprecise Probability and Least Favorable Models
And Supplements to the Article
Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'07) [July 16th - 19th 2007, Prague, Czech Republic]