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The digital transformation with its new technologies and customer expectation has a significant effect on the customer channels in the insurance industry. The objective of this study is the identification of enabling and hindering factors for the adoption of online claim notification services that are an important part of the customer experience in insurance. For this purpose, we conducted a quantitative cross-sectional survey based on the exemplary scenario of car insurance in Germany and analyzed the data via structural equation modeling (SEM). The findings show that, besides classical technology acceptance factors such as perceived usefulness and ease of use, digital mindset and status quo behavior play a role: acceptance of digital innovations, lacking endurance as well as lacking frustration tolerance with the status quo lead to a higher intention for use. Moreover, the results are strongly moderated by the severity of the damage event—an insurance-specific factor that is sparsely considered so far. The latter discovery implies that customers prefer a communication channel choice based on the individual circumstances of the claim.
In this paper we describe the selection of a modern build automation tool for an industry research partner of ours, namely an insurance company. Build automation has become increasingly important over the years. Today, build automation became one of the central concepts in topics such as cloud native development based on microservices and DevOps. Since more and more products for build automation have entered the market and existing tools have changed their functional scope, there is nowadays a large number of tools on the market that differ greatly in their functional scope. Based on requirements from our partner company, a build server analysis was conducted. This paper presents our analysis requirements, a detailed look at one of the examined tools and a summarized comparison of two tools.
Background:
Many patients with cardiovascular disease also show a high comorbidity of mental disorders, especially such as anxiety and depression. This is, in turn, associated with a decrease in the quality of life. Psychocardiological treatment options are currently limited. Hence, there is a need for novel and accessible psychological help. Recently, we demonstrated that a brief face-to-face metacognitive therapy (MCT) based intervention is promising in treating anxiety and depression. Here, we aim to translate the face-to-face approach into digital application and explore the feasibility of this approach.
Methods:
We translated a validated brief psychocardiological intervention into a novel non-blended web app. The data of 18 patients suffering from various cardiac conditions but without diagnosed mental illness were analyzed after using the web app over a two-week period in a feasibility trial. The aim was whether a nonblended web app based MCT approach is feasible in the group of cardiovascular patients with cardiovascular disease.
Results:
Overall, patients were able to use the web app and rated it as satisfactory and beneficial. In addition, there was first indication that using the app improved the cardiac patients’ subjectively perceived health and reduced their anxiety. Therefore, the approach seems feasible for a future randomized controlled trial.
Conclusion:
Applying a metacognitive-based brief intervention via a nonblended web app seems to show good acceptance and feasibility in a small target group of patients with CVD. Future studies should further develop, improve and validate digital psychotherapy approaches, especially in patient groups with a lack of access to standard psychotherapeutic care.
Dramatic increases in the number of cyber security attacks and breaches toward businesses and organizations have been experienced in recent years. The negative impacts of these breaches not only cause the stealing and compromising of sensitive information, malfunctioning of network devices, disruption of everyday operations, financial damage to the attacked business or organization itself, but also may navigate to peer businesses/organizations in the same industry. Therefore, prevention and early detection of these attacks play a significant role in the continuity of operations in IT-dependent organizations. At the same time detection of various types of attacks has become extremely difficult as attacks get more sophisticated, distributed and enabled by Artificial Intelligence (AI). Detection and handling of these attacks require sophisticated intrusion detection systems which run on powerful hardware and are administered by highly experienced security staff. Yet, these resources are costly to employ, especially for small and medium-sized enterprises (SMEs). To address these issues, we developed an architecture -within the GLACIER project- that can be realized as an in-house operated Security Information Event Management (SIEM) system for SMEs. It is affordable for SMEs as it is solely based on free and open-source components and thus does not require any licensing fees. Moreover, it is a Self-Contained System (SCS) and does not require too much management effort. It requires short configuration and learning phases after which it can be self-contained as long as the monitored infrastructure is stable (apart from a reaction to the generated alerts which may be outsourced to a service provider in SMEs, if necessary). Another main benefit of this system is to supply data to advanced detection algorithms, such as multidimensional analysis algorithms, in addition to traditional SIEMspecific tasks like data collection, normalization, enrichment, and storage. It supports the application of novel methods to detect security-related anomalies. The most distinct feature of this system that differentiates it from similar solutions in the market is its user feedback capability. Detected anomalies are displayed in a Graphical User Interface (GUI) to the security staff who are allowed to give feedback for anomalies. Subsequently, this feedback is utilized to fine-tune the anomaly detection algorithm. In addition, this GUI also provides access to network actors for quick incident responses. The system in general is suitable for both Information Technology (IT) and Operational Technology (OT) environments, while the detection algorithm must be specifically trained for each of these environments individually.
Data Mining Verfahren
(2008)
Der vorliegende Forschungsbericht dokumentiert Ergebnisse, die in der Abteilung Informatik der Fakultät Wirtschaft und Informatik der Fachhochschule Hannover im Sommersemesters 2007 im Rahmen eines von der Forschungskommission genehmigten Forschungssemesters vom Autor erarbeitet wurden. Der Bericht stellt die wichtigsten Verfahren aus dem Gebiet des Data Minings vor, diskutiert auf der Basis von selbst programmierten Beispielen die Eignung der verschiedenen Verfahren für die entsprechenden Anwendungsgebiete und vergleicht die speziellen Eigenschaften der entsprechenden Algorithmen.
Die computergestützte Erkennung von Personen basiert auf der quantitativen Feststellung einer möglichst weitgehenden Übereinstimmung zwischen einer gespeicherten Graphik und dem momentan erfassten Kamerabild. Der vorliegende Forschungsbericht beschreibt ein solches Erkennungssystem, das auf der optimalen Kombination unterschiedlicher, sich gegenseitig ergänzender Erkennungsverfahren beruht. Im Zentrum des Erkennungssystems arbeitet als wesentliche Komponente ein neuronales Netz.
Für das digitale Flugführungssystem des Versuchsflugzeugs HFB 320 wurde am Institut für Flugführung der DFVLR in Braunschweig eine Betriebsart zum automatischen zeitgenauen Fliegen im Flughafen-Nahbereich entwickelt und im Flugversuch erprobt. Der Bericht enthält die Beschreibung der eingesetzten Algorithmen zur Berechnung 4-dimensionaler Flugbahnen unter Berücksichtigung der momentanen Windsituation. Es werden verschiedene Verfahren zur Messung, Filterung und Vorhersage des Windvektors entwickelt und an Hand von Flugversuchsergebnissen diskutiert.
Report of a research project of the Fachhochschule Hannover, University of Applied Sciences and Arts, Department of Information Technologies. Automatic face recognition increases the security standards at public places and border checkpoints. The picture inside the identification documents could widely differ from the face, that is scanned under random lighting conditions and for unknown poses. The paper describes an optimal combination of three key algorithms of object recognition, that are able to perform in real time. The camera scan is processed by a recurrent neural network, by a Eigenfaces (PCA) method and by a least squares matching algorithm. Several examples demonstrate the achieved robustness and high recognition rate.
Autonomous mobile six-legged robots are able to demonstrate the potential of intelligent control systems based on recurrent neural networks. The robots evaluate only two forward and two backward looking infrared sensor signals. Fast converging genetic training algorithms are applied to train the robots to move straight in six directions. The robots performed successfully within an obstacle environment and there could be observed a never trained useful interaction between each of the single robots. The paper describes the robot systems and presents the test results. Video clips are downloadable under www.inform.fh-hannover.de/download/lechner.php. Held on IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003, April 2003, Portugal).
Zeitarbeit ist eine Boombranche. Zeitarbeit ist prekäre Beschäftigung. Mit Zeitarbeit wird Missbrauch getrieben. Zeitarbeit ist wichtig. Jeder, der die öffentliche Diskussion verfolgt, hat einen dieser Sätze schon einmal gehört. Wir reden über Zeitarbeit, wie über die Frage, ob Entlohnung gut oder schlecht ist. Vergessen wird dabei oft, dass Zeitarbeit nicht gleich Zeitarbeit ist, sondern sich Motive und Einsatz der Zeitarbeit von Unternehmen zu Unternehmen deutlich unterscheiden können. So kann ein Personaldienstleister Hausfrauen an eine Versicherung vermitteln, um dort für die Reinigung und Sauberkeit der Büros zu sorgen. Ebenso kann ein Ingenieurbüro eigene Mitarbeiter an eine Kraftwerksfirma verleihen, um hochspezielle Projektaufgaben an einem Solarkraftwerk zu verrichten.
Und genau darum geht es, wenn wir die Zukunft der Zeitarbeit gestalten wollen: herauszufinden, unter welchen Bedingungen und für welche Zwecke Zeitarbeit in Unternehmen eingesetzt wird und was ihre Nutzung fördert bzw. behindert. Um darauf eine Antwort zu haben, muss man zunächst die Verschiedenartigkeit der Zeitarbeit anerkennen. Im Anschluss daran muss man herausfinden, welchen Typ Zeitarbeit man in einem bestimmten Unternehmen vor sich hat, wovon dieser beeinflusst wird und was man anders oder besser machen kann. Es geht in diesem Beitrag also zuallererst darum, Motive der Zeitarbeitsnutzung herauszuarbeiten und zu untersuchen, wie sie zu verschiedenen Formen des Zeitarbeitseinsatzes in Unternehmen führen.