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Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today’s corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.
The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated
structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.
Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.
This book brings together experts from research and practice. It includes the design of innovative Robot Process Automation (RPA) concepts, the discussion of related research fields (e.g., Artificial Intelligence, AI), the evaluation of existing software products, and findings from real-life implementation projects. Similar to the substitution of physical work in manufacturing (blue collar automation), Robotic Process Automation tries to substitute intellectual work in office and administration processes with software robots (white-collar automation). The starting point for the development of RPA was the observation that - despite the use of process-oriented enterprise systems (such as ERP, CRM and BPM systems) - additional manual activities are still indispensable today. In the RPA approach, these manual activities are learned and automated by software robots, either by defining rules or by observing manual activities. RPA is related to business process management, machine learning, and artificial intelligence. Tools for RPA originated from dedicated stand-alone software. Today, RPA functionalities are also integrated into elaborated process management suites. From a conceptual perspective, RPA can be structured into input components (sensors in the wide sense), an intelligence center, and output components (actuators in the wide sense). From a strategic perspective, the impact of RPA can be related to the support of existing tasks, the complete substitution of human activities, and the innovation of processes as well as business models. At present, high expectations are related to the use of RPA in the improvement of software-supported business processes. Manual activities are learned and automated by software robots that interact with existing applications via the presentation layer. In combination with artificial intelligence (AI) as well as innovative interfaces (e. g., voice recognition) RPA creates a novel level of automation for office and administration processes. Its benefit potential reaches a return on investment (ROI) up-to 800% that is documented in various case studies.
After a liver tumor intervention the medical doctor has to compare both pre and postoperative CT acquisitions to ensure that all carcinogenic cells are destroyed. A correct assessment of the intervention is of vital importance, since it will reduce the probability of tumor recurrence. Some methods have been proposed to support the medical doctors during the assessment process, however, all of them focus on secondary tumors. In this paper a tool is presented that enables the outcome validation for both primary and secondary tumors. Therefore, a multiphase registration (preoperative arterial and portal phases) followed by a registration between the pre and postoperative CT images is carried out. The first registration is in charge of the primary tumors that are only visible in the arterial phase. The secondary tumors will be incorporated in the second registration step. Finally, the part of the tumor that was not covered by the necrosis is quantified and visualized. The method has been tested in 9 patients, with an average registration error of 1.41 mm.
Das Forschungsprojekt Produktionseffizienz in der Kleinserie (ProeK) erarbeitet kostengünstige und effiziente Lösungsansätze für Prozessketten im Zukunftsfeld der Elektromobilität. Das Teilprojekt Karosserie setzt diese Zielsetzung durch innovative und praxisorientierte Produkt- und Prozesskonzepte mit neuartigen bauteilintegrierten Vorrichtungsfunktionen (BiV) um. Im Teilprojekt Außenhaut sollen Toleranzen adaptiv durch Anpassungen der Prozessparameter sowie Bauteilmanipulation kompensiert werden.
False spectra formation in the differential two-channel scheme of the laser Doppler flowmeter
(2018)
Noise in the differential two-channel scheme of a classic laser Doppler flowmetry (LDF) instrument was studied. Formation of false spectral components in the output signal due to beating of electrical signals in the differential amplifier was found out. The improved block-diagram of the flowmeter was developed allowing to reduce the noise.
Prosthetic textile implants of different shapes, sizes and polymers are used to correct the apical prolapse after hysterectomy (removal of the uterus). The selection of the implant before or during minimally invasive surgery depends on the patient’s anatomical defect, intended function after reconstruction and most importantly the surgeon’s preference. Weakness or damage of the supporting tissues during childbirth, menopause or previous pelvic surgeries may put females in higher risk of prolapse. Numerical simulations of reconstructed pelvic floor with weakened tissues and organ supported by textile product models: DynaMesh®-PRS soft, DynaMesh®-PRP soft and DynaMesh®-CESA from FEG Textiletechnik mbH, Germany are compared.
The porosity of surgical meshes makes them flexible for large elastic deformation and establishes the healing conditions of good tissue in growth. The biomechanic modeling of orthotropic and compressible materials requires new materials models and simulstaneoaus fit of deformation in the load direction as well as trannsversely to to load. This nonlinear modeling can be achieved by an optical deformation measurement. At the same time the full field deformation measurement allows the dermination of the change of porosity with deformation. Also the socalled effective porosity, which has been defined to asses the tisssue interatcion with the mesh implants, can be determined from the global deformation of the surgical meshes.