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Analyzing and modeling the latency and jitter behavior of mixed industrial TSN and DetNet networks
(2022)
Recently the production of electric cars is increasing worldwide. The main target is to lower the greenhouse gas emissions. Even if an electrified vehicle is locally emission-free the manufacturing of lithium ion batteries are producing significant amounts of CO2. In order to decrease the air pollution governments are considering recycling programs to extend battery life and usage of important raw materials. A new approach to recover LiNixMnyCozO2 (NMC) particles while saving the chemical and morphological properties using water was presented by Tim Sieber et al. [1]. With the presented study, we are focusing on the analysis of the effects on the Global Warming Potential (GWP) for the water based recycling process based on a reuse of NMC material in new batteries.
It is possible to reduce the ecological damage of the manufacturing process of Li-Ion battery cells even with little amounts of recovered cathode material that is used for the production of new battery cells. Based on the suggestion that 95% of the NMC cathode material can be recovered by the hydrometallurgical recovery and the reuse of 10% within the production of new batteries a reduction of the GWP by 7% ,can be identified for the cathode materials. For other impact categories such as Acidification Potential (AP), Eutrophication Potential (EP), and Photochemical Ozone Creation Potential (POCP), savings of 10%, 11%, and 8 % can be achieved respectively.
The studied water based recycling process can be quoted as environment-friendly and leads to a reduction of all impact categories by a re-use of 10% recovered NMC material. Based on this knowledge an additional recycling on substance level is recommended.
This paper provides an analysis of the trend in autonomous driving traffic and the development of infrastructural support, whereas the requirements on the infrastructural support will be analyzed. Then selected traffic scenes will be implemented in an autonomous driving simulator tool in order to figure out the required parameters to assist the autonomous vehicle from the infrastructure.
Optimization of EMI filter with consideration of the noise source impedance for DC/DC converter
(2021)
Why Kappa Regression?
(2021)
Under Construction!
(2020)
Designing the OR cockpit
(2021)
Coverage Probability of Methods for Steady-State Availability Inference with a Confidence Interval
(2021)
Systematic and user-oriented development of physical interface for vehicle ultrafast charging
(2022)
Negotiations are a relevant and highly complex business skill. Therefore, extensive training is required to become a good negotiator. Such training is offered by universities for their students and by companies for their employees. The present paper designs gamified feedback features in electronic negotiation training and evaluates their potential and their effects. Following a design science research method, feedback mechanisms in electronic negotiation training are derived from literature. An assessment regarding their relevance for e-negotiation training shows a preparation quiz, set and track goals and expert reviews to be the most useful gamified feedback mechanisms. Dedicated mock-ups implementing these feedback mechanisms are designed and evaluated in semi-structured interviews showing their capability to improve relevant negotiation skills, as well as motivation and competence of the learners. Out of the three mock-ups, the interviewees prefer the feedback mechanisms “expert review” and “set and track goals”; both mechanisms provide a competence-confirming learning experience and an autonomous learning experience.