Elektrotechnik und Informatik (ETI)
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Cathode ray-luminescent phosphor and method for the preparation thereof, <b>United States Patent</b>
(2000)
Background: Modern healthcare devices can be connected to computer networks and many western healthcareinstitutions run those devices in networks. At the same time, cyber attacks are on the rise and there is evidence thatcybercriminals do not spare critical infrastructure such as major hospitals, even if they endanger patients. Intuitively,the more and closer connected healthcare devices are to public networks, the higher the risk of getting attacked.
Methods: To asses the current connectivity status of healthcare devices, we surveyed the field of German hospitalsand especially University Medical Center UMCs.
Results: The results show a strong correlation between the networking degree and the number of medical devices.The average number of medical devices is 25.150, with a median of networked medical devices of 3.600. Actual keyusers of networked medical devices are the departments Radiology, Intensive Care, Radio-Oncology RO, NuclearMedicine NUC, and Anaesthesiology in the group of UMCs. In the next five years, the usage of networked medicaldevices will increase significantly in the departments of Surgery, Intensive Care, and Radiology. We detected a strongcorrelation between the degree of connectivity and the likelihood of being attacked.The survey answers regarding the cyber security status reveal a lack of security basics in some of the inquiredhospitals. We did discover successful attacks in hospitals with separated or subsidiary departments. A fusion ofcompetencies on an organizational level facilitates the right behavior here. Most hospitals rated themselvespredominantly positively in the self-assessment but also stated the usefulness of IT security insurance.Conclusions:Concluding our results, hospitals are already facing the consequences of omitted measures within theirgrowing pool of medical devices. Continuously relying on historically grown structures without adaption and trustingmanufactures to solve vectors is a critical behavior that could seriously endanger patients.
Technical and organizational steps are necessary to mitigate cyber threats and reduce risks. Human behavior is the last line of defense for many hospitals and is considered as equally important as technical security. Medical staff must be properly trained to perform such procedures. This paper presents the first qualitative, interdisciplinary research on how members of an intermediate care unit react to a cyberattack against their patient monitoring equipment. We conducted a simulation in a hospital training environment with 20 intensive care nurses. By the end of the experiment, 12 of the 20 participants realized the monitors’ incorrect behavior. We present a qualitative behavior analysis of high performing participants (HPP) and low performing participants (LPP). The HPP showed fewer signs of stress, were easier on their colleagues, and used analog systems more often than the LPP. With 40% of our participants not recognizing the attack, we see room for improvements through the use of proper tools and provision of adequate training to prepare staff for potential attacks in the future.
Sichere ABAP-Programmierung
(2009)
Camera based path planning for low quantity - high variant manufacturing with industrial robots
(2019)
The acquisition costs for industrial robots have been steadily decreasing in past years. Nevertheless, they still face significant drawbacks in the required effort for the preparation of complex robot tasks which causes these systems to be rarely present so far in small and medium-sized enterprises (SME) that focus mainly on small volume, high variant manufacturing. In this paper, we propose a camera-based path planning framework that allows the fast preparation and execution of robot tasks in dynamic environments which leads to less planning overhead, fast program generation and reduced cost and hence overcomes the major impediments for the usage of industrial robots for automation in SMEs with focus on low volume and high variant manufacturing. The framework resolves existing problems in different steps. The exact position and orientation of the workpiece are determined from a 3D environment model scanned by an optical sensor. The so retrieved information is used to plan a collision-free path that meets the boundary conditions of the specific robot task. Experiments show the potential and effectiveness of the the framework presented here by evaluating a case study.
Accurate self-localisation is a fundamental ability of any mobile robot. In Monte Carlo localisation, a probability distribution over a space of possible hypotheses accommodates the inherent uncertainty in the position estimate, whereas bounded-error localisation provides a region that is guaranteed to contain the robot. However, this guarantee is accompanied by a constant probability over the confined region and therefore the information yield may not be sufficient for certain practical applications. Four hybrid localisation algorithms are proposed, combining probabilistic filtering with non-linear bounded-error state estimation based on interval analysis. A forward-backward contractor and the Set Inverter via Interval Analysis are hybridised with a bootstrap filter and an unscented particle filter, respectively. The four algorithms are applied to global localisation of an underwater robot, using simulated distance measurements to distinguishable landmarks. As opposed to previous hybrid methods found in the literature, the bounded-error state estimate is not maintained throughout the whole estimation process. Instead, it is only computed once in the beginning, when solving the wake-up robot problem, and after kidnapping of the robot, which drastically reduces the computational cost when compared to the existing algorithms. It is shown that the novel algorithms can solve the wake-up robot problem as well as the kidnapped robot problem more accurately than the two conventional probabilistic filters.