The Value of IS to Ensure the Security of Energy Supply – The Case of Electric Vehicle Charging

Replacing the internal combustion engine through electrification is regarded as crucial for future mobility. However, the interactions between a higher number of electric vehicles and the impacts on power plant capacities have not yet been sufficiently investigated. Hence, this paper develops an approach to evaluate the energetic impacts on current power plant capacities that result from a higher market penetration of electric vehicles by 2030. The key aspect of the approach is the quantification of smart charging processes in energetic and economic perspectives. It was found that the implementation has significant energetic and thus economic benefits because of an improved integration of the additional electricity demand. The value of information systems which enable smart charging processes is shown by the calculated cost-saving potentials, resulting from a reduced expansion of the power plant system

Content Management von Leittexten mit XML Topic Maps

Die Autoren definieren den Umgang mit internet- basierten Informations- und Kommunikationstechnologien als Schlüsselqualifikation für Studierende aller Fachrichtungen. Im vorliegenden Aufsatz beschreiben sie ein Projekt, das der Fachbereich Erziehungswissenschaften der Universität Heidelberg seit 2001 durchführt. Hier werden Studierende der Geistes- und Sozialwissenschaften zu "Lernberatern" ausgebildet, die als Multiplikatoren die notwendigen Kenntnisse erwerben. Die Teilnehmenden erarbeiten nach der "Leittextmethode" selbstgesteuert xml-basierte Contents. Dies setzt den Erwerb von informationstechnischen Kenntnissen voraus, der neben dem Aufbau eines (sowohl technischen als auch sozialen) Netzwerks einen Schwerpunkt bildet

Attribution von Verantwortung durch Metaphernanalyse

Die interdisziplinäre technikethische Arbeit analysiert die Bedeutung der folgenden forschungsleitenden Fragen: 'Wer ist verantwortlich, wenn der Computer einen Fehler macht?', und: 'Wie kann der Computer verantwortlich gestaltet und eingesetzt werden?' Die Arbeit verbindet die folgenden drei Perspektiven: (1) Was ist mit dem Begriff der Verantwortung gemeint? Sprachanalytische Bedeutungsanalysen ergeben: Verantwortung ist eine Rechenschaftspflicht, die aus Sorgepflichten entsteht. Ein Computer kann kein Verantwortungssubjekt sein, insofern er nicht fähig ist zur Sorge ist. (2) Was ist hier mit dem Begriff des Computers gemeint? Welche epistemische und normative Rolle erfüllen typische Computer-Metaphern wie 'Werkzeug', 'Maschine' oder 'Partner' in der Zuschreibung von Verantwortung? (3) Welche Distribution von Verantwortung besteht zwischen Entwicklern und Nutzern von Softwaresystemen? Auf Grundlage der vorhergehenden Metaphernanalyse sowie einer Rekonstruktion informatischen beruflichen Handelns werden zwei sich ergänzende Gestaltungsstrategien für Softwaresysteme beschrieben und bewertet. -- Die Arbeit spannt einen Bogen zwischen Themen, die im deutschen Hochschulsystem gewöhnlich eher separiert werden. Neben der Bearbeitung der eigentlichen Sachfrage bestand eine wesentliche Aufgabe darin, den Bruch zwischen natur- und geisteswissenschaftlichem Wissenschaftsverständnis methodisch versuchsweise zu überbrücken. -- Die Arbeit wird gleichzeitig veröffentlicht als Bericht des Wilhelm-Schickard-Instituts für Informatik, Universität Tübingen, WSI-99-14, ISSN 0946-3852. Weitere Formate und näheres zur Arbeit unter http://www-pu.informatik.uni-tuebingen.de/users/busse/diss

Inhalte, Kontexte und Mediendidaktik in 'Informatik und Gesellschaft'

Veröffentlichung des Wilhelm-Schickard-Institut für Informatik Universität Tübinge

Medienkompetenz - Kompetenz für neue Medien:Studie im Auftrag des Forum Bildung ; Workshop am 14. September 2001 in Berlin

<br

Professional knowledge of (prospective) Mathematics Teachers – Its structure and development

Recent research on the professional knowledge of mathematics teachers, which has been carried out in the last decade, is in the focus of this paper. Building on the international IEA Teacher Education and Development Study – Learning to Teach Mathematics (TEDS-M), this paper describes a more situated way of evaluating the professional knowledge of teachers. The theoretical framework of the follow-up study of TEDS-M takes up the novice-expert framework andanalyses via video-based assessment instruments the structure and development of the professional knowledge of mathematics teachers. More recent concepts on noticing and interpreting classroom situations and students’ activities are also incorporated into the analysis. Connecting the results of the study TEDS-FU with the study TEDS-M gives insight into the development of the professional knowledge of mathematics teachers

Professional knowledge of (prospective) Mathematics Teachers – Its structure and development

Recent research on the professional knowledge of mathematics teachers, which has been carried out in the last decade, is in the focus of this paper. Building on the international IEA Teacher Education and Development Study – Learning to Teach Mathematics (TEDS-M), this paper describes a more situated way of evaluating the professional knowledge of teachers. The theoretical framework of the follow-up study of TEDS-M takes up the novice-expert framework andanalyses via video-based assessment instruments the structure and development of the professional knowledge of mathematics teachers. More recent concepts on noticing and interpreting classroom situations and students’ activities are also incorporated into the analysis. Connecting the results of the study TEDS-FU with the study TEDS-M gives insight into the development of the professional knowledge of mathematics teachers

Development and Processing of Continuous Flax and Carbon Fiber-Reinforced Thermoplastic Composites by a Modified Material Extrusion Process

Additive manufacturing, especially material extrusion (MEX), has received a lot of attention recently. The reasons for this are the numerous advantages compared to conventional manufacturing processes, which result in various new possibilities for product development and -design. By applying material layer by layer, parts with complex, load-path optimized geometries can be manufactured at neutral costs. To expand the application fields of MEX, high-strength and simultaneously lightweight materials are required which fulfill the requirements of highly resilient technical parts. For instance, the embedding of continuous carbon and flax fibers in a polymer matrix offers great potential for this. To achieve the highest possible variability with regard to the material combinations while ensuring simple and economical production, the fiber-matrix bonding should be carried out in one process step together with the actual parts manufacture. This paper deals with the adaptation and improvement of the 3D printer on the one hand and the characterization of 3D printed test specimens based on carbon and flax fibers on the other hand. For this purpose, the print head development for in-situ processing of contin uous fiber-reinforced parts with improved mechanical properties is described. It was determined that compared to neat polylactic acid (PLA), the continuous fiber-reinforced test specimens achieve up to 430% higher tensile strength and 890% higher tensile modulus for the carbon fiber reinforcement and an increase of up to 325% in tensile strength and 570% in tensile modulus for the flax fibers. Similar improvements in performance were achieved in the bending tests

Road pavement crack detection using deep learning with synthetic data

The improvement of road system quality is a critical task. The mechanism to address such important issue is close monitoring of road pavement condition. Traditional approach requires manual identification of damages. Taking into account considerable length of road system it is essential to create an effective automatic pavement defects detection tool. This approach will extremely reduce time for monitoring of current road state. In this paper global experience in solution of detection issues of road pavement's distress is reviewed. The article includes information about the existing datasets of road defects, which are commonly used for detection and segmentation. The present work is based on deep learning approach with the use of synthetic generated training data for segmentation of cracks in driver-view image. The novelty of the approach lies in creating synthetic dataset for training state-of-the-art deep learning frameworks. The relevance of the research is emphasized by processing of wide-view images in which heterogeneous pixel intensity, complex crack topology, different illumination condition and complexity of background make the task challenging

Impact of home-based training and nutritional behavior on body composition and metabolic markers in cancer patients: data from the CRBP-TS study

IntroductionObesity and physical inactivity are known to affect cancer's development and prognosis. In this context, physical aerobic and resistance training as well as a Mediterranean nutrition have been proven to have many positive health effects. The aim of this study was therefore to investigate the effect of home-based training on body composition and certain metabolic laboratory parameters.MethodsPatients with breast, colorectal and prostate cancer who underwent curative surgery at stages T1N0M0–T3N3M0 were eligible for this trial and randomized to an intervention and control group. In the intervention group the patients carried out online-based strength-endurance home training during the 6-month study period. Body composition was assessed via bioelectrical impedance analysis (baseline, 3 months and 6 months). Metabolic blood parameters were also analyzed and nutrition behavior determined using the Mediterranean Diet Adherence Screener (MEDAS).ResultsThe intervention group's fat mass decreased while their lean body mass increased (time effect p = 0.001 and p = 0.001, respectively). We found no interaction effect in body weight (p = 0.19), fat mass [p = 0.06, 6-months estimates −0.9 (95% CI −1.8 to −0.1)] and lean body mass (p = 0.92). Blood samples also failed to show a statistically significant interaction effect between time × group for HbA1c% (p = 0.64), Insulin (p = 0.33), Adiponectin (p = 0.87), Leptin (p = 0.52) and Triglycerides (p = 0.43). Only Adiponectin revealed significance in the time effect (p &lt; 0.001) and Leptin in the group effect (p = 0.03). Dietary behavior during the study period was similar in patients in the intervention and control groups (interaction p = 0.81; group p = 0.09 and time p = 0.03).DiscussionIndividualized online-based home training in postoperative cancer patients revealed only minor changes, with no group differences in body composition or metabolic laboratory parameters, which were predominantly in the reference range at baseline. More studies investigating effects of online-based home training on body composition and nutrition behavior are needed.Trial registrationhttps://drks.de/search/en/trial/DRKS00020499, DRKS-ID: DRKS00020499