Entwicklung eines Neukundenakquisitionskonzeptes auf Basis einer Zielkundenstrategie für Unternehmen der mittelständischen Druckindustrie am Beispiel der Firma Lipp GmbH, Graphische Betriebe

Zusammenfassung / Ziele der Arbeit: 1) Darlegung der Differenzierung als vielversprechendste Wettbewerbsstrategie in der mittelständischen Druckindustrie 2) Erarbeitung einer Methodik zur Definition geeigneter Kunden(-gruppen) für ein Unternehmen der mittelständischen Druckindustrie. 3) Ableitung eines Konzeptes für die Neukundenakquisition inklusive individualisierter Ansprache und Verhaltensrichtlinien für den Kontakt. 4) Implementierung des Konzeptes in die bestehenden Vertriebsstruktur der Firma Lipp GmbH, graphische Betriebe

Block Crossings in Storyline Visualizations

Storyline visualizations help visualize encounters of the characters in a story over time. Each character is represented by an x-monotone curve that goes from left to right. A meeting is represented by having the characters that participate in the meeting run close together for some time. In order to keep the visual complexity low, rather than just minimizing pairwise crossings of curves, we propose to count block crossings, that is, pairs of intersecting bundles of lines. Our main results are as follows. We show that minimizing the number of block crossings is NP-hard, and we develop, for meetings of bounded size, a constant-factor approximation. We also present two fixed-parameter algorithms and, for meetings of size 2, a greedy heuristic that we evaluate experimentally.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Machine Learning for Optical Network Security Monitoring: A Practical Perspective

In order to accomplish cost-efficient management of complex optical communication networks, operators are seeking automation of network diagnosis and management by means of Machine Learning (ML). To support these objectives, new functions are needed to enable cognitive, autonomous management of optical network security. This paper focuses on the challenges related to the performance of ML-based approaches for detectionand localization of optical-layer attacks, and to their integration with standard Network Management Systems (NMSs). We propose a framework for cognitive security diagnostics that comprises an attack detection module with Supervised Learning (SL), Semi-Supervised Learning (SSL) and Unsupervised Learning (UL) approaches, and an attack localization module that deduces the location of a harmful connection and/or a breached link. The influence of false positives and false negatives is addressed by a newly proposed Window-based Attack Detection (WAD) approach. We provide practical implementation\ua0guidelines for the integration of the framework into the NMS and evaluate its performance in an experimental network testbed subjected to attacks, resulting with the largest optical-layer security experimental dataset reported to date

SIMPL: Secure IoT Management Platform

The proliferation of IoT devices is increasing at a fast pace, whether for private or business use. However, despite their growing popularity, their safe operation is often not guaranteed. To tackle the security challenges of modern IoT environments, the German Federal Ministry of Education and Research is funding the SIMPL project in order to support research in this area. The contribution of this paper is to introduce the main goal, objectives, and key features of SIMPL

Demonstration of Machine-Learning-Assisted Security Monitoring in Optical Networks

We report on the first demonstration of machine-learning-assisted detection, identification and localisation of optical-layer attacks integrated into network management system and verified on real-life experimental attack traces from a network operator testbed

Instrumental Assessment of Stepping in Place Captures Clinically Relevant Motor Symptoms of Parkinson’s Disease

Fluctuations of motor symptoms make clinical assessment in Parkinson's disease a complex task. New technologies aim to quantify motor symptoms, and their remote application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson's disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman's Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson's disease. The simple technical test setup would allow future use by patients themselves

Clinical autonomic nervous system laboratories in Europe: a joint survey of the European Academy of Neurology and the European Federation of Autonomic Societies

© 2022 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Background and purpose: Disorders of the autonomic nervous system (ANS) are common conditions, but it is unclear whether access to ANS healthcare provision is homogeneous across European countries. The aim of this study was to identify neurology-driven or interdisciplinary clinical ANS laboratories in Europe, describe their characteristics and explore regional differences. Methods: We contacted the European national ANS and neurological societies, as well as members of our professional network, to identify clinical ANS laboratories in each country and invite them to answer a web-based survey. Results: We identified 84 laboratories in 22 countries and 46 (55%) answered the survey. All laboratories perform cardiovascular autonomic function tests, and 83% also perform sweat tests. Testing for catecholamines and autoantibodies are performed in 63% and 56% of laboratories, and epidermal nerve fiber density analysis in 63%. Each laboratory is staffed by a median of two consultants, one resident, one technician and one nurse. The median (interquartile range [IQR]) number of head-up tilt tests/laboratory/year is 105 (49-251). Reflex syncope and neurogenic orthostatic hypotension are the most frequently diagnosed cardiovascular ANS disorders. Thirty-five centers (76%) have an ANS outpatient clinic, with a median (IQR) of 200 (100-360) outpatient visits/year; 42 centers (91%) also offer inpatient care (median 20 [IQR 4-110] inpatient stays/year). Forty-one laboratories (89%) are involved in research activities. We observed a significant difference in the geographical distribution of ANS services among European regions: 11 out of 12 countries from North/West Europe have at least one ANS laboratory versus 11 out of 21 from South/East/Greater Europe (p = 0.021). Conclusions: This survey highlights disparities in the availability of healthcare services for people with ANS disorders across European countries, stressing the need for improved access to specialized care in South, East and Greater Europe.info:eu-repo/semantics/publishedVersio

EFAS/EAN survey on the influence of the COVID-19 pandemic on European clinical autonomic education and research

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Purpose: To understand the influence of the coronavirus disease 2019 (COVID-19) pandemic on clinical autonomic education and research in Europe. Methods: We invited 84 European autonomic centers to complete an online survey, recorded the pre-pandemic-to-pandemic percentage of junior participants in the annual congresses of the European Federation of Autonomic Societies (EFAS) and European Academy of Neurology (EAN) and the pre-pandemic-to-pandemic number of PubMed publications on neurological disorders. Results: Forty-six centers answered the survey (55%). Twenty-nine centers were involved in clinical autonomic education and experienced pandemic-related didactic interruptions for 9 (5; 9) months. Ninety percent (n = 26/29) of autonomic educational centers reported a negative impact of the COVID-19 pandemic on education quality, and 93% (n = 27/29) established e-learning models. Both the 2020 joint EAN-EFAS virtual congress and the 2021 (virtual) and 2022 (hybrid) EFAS and EAN congresses marked higher percentages of junior participants than in 2019. Forty-one respondents (89%) were autonomic researchers, and 29 of them reported pandemic-related trial interruptions for 5 (2; 9) months. Since the pandemic begin, almost half of the respondents had less time for scientific writing. Likewise, the number of PubMed publications on autonomic topics showed the smallest increase compared with other neurological fields in 2020-2021 and the highest drop in 2022. Autonomic research centers that amended their trial protocols for telemedicine (38%, n = 16/41) maintained higher clinical caseloads during the first pandemic year. Conclusions: The COVID-19 pandemic had a substantial negative impact on European clinical autonomic education and research. At the same time, it promoted digitalization, favoring more equitable access to autonomic education and improved trial design.info:eu-repo/semantics/publishedVersio

Faster Force-Directed Graph Drawing with the Well-Separated Pair Decomposition

The force-directed paradigm is one of the few generic approaches to drawing graphs. Since force-directed algorithms can be extended easily, they are used frequently. Most of these algorithms are, however, quite slow on large graphs, as they compute a quadratic number of forces in each iteration. We give a new algorithm that takes only O ( m + n log n ) time per iteration when laying out a graph with n vertices and m edges. Our algorithm approximates the true forces using the so-called well-separated pair decomposition. We perform experiments on a large number of graphs and show that we can strongly reduce the runtime, even on graphs with less than a hundred vertices, without a significant influence on the quality of the drawings (in terms of the number of crossings and deviation in edge lengths)

Faster Force-Directed Graph Drawing with the Well-Separated Pair Decomposition

The force-directed paradigm is one of the few generic approaches to drawing graphs. Since force-directed algorithms can be extended easily, they are used frequently. Most of these algorithms are, however, quite slow on large graphs as they compute a quadratic number of forces in each iteration. We speed up this computation by using an approximation based on the well-separated pair decomposition. We perform experiments on a large number of graphs and show that we can strongly reduce the runtime—even on graphs with less then a hundred vertices—without a significant influence on the quality of the drawings (in terms of number of crossings and deviation in edge lengths)