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Article
Open AccessDisentangling the black box around CEO and financial information-based accounting fraud detection: machine learning-based evidence from publicly listed U.S. firms
This study investigates the predictive power of CEO characteristics on accounting fraud utilizing a machine learning approach. Grounded in upper echelons theory, we show the predictive value of widely neglecte...
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Chapter and Conference Paper
Generation of Consistent Slip, Trip and Fall Kinematic Data via Instability Detection and Recovery Performance Analysis for Use in Machine Learning Algorithms for (Near) Fall Detection
Slip, trip and fall (STF) accidents are a major problem for companies in many industries and cause massive work absences. According to the German employers' liability insurance associations, this type of accid...
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Chapter and Conference Paper
Well-Balanced and Asymptotic Preserving IMEX-Peer Methods
Peer methods are a comprehensive class of time integrators offering numerous degrees of freedom in their coefficient matrices that can be used to ensure advantageous properties, e.g. A-stability or super-conve...
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Article
Open AccessCorrection to: Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI
The article Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI
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Article
Open AccessConsensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI
Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexpon...
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Chapter and Conference Paper
ZLiTE: Lightweight Clients for Shielded Zcash Transactions Using Trusted Execution
Cryptocurrencies record transactions between parties in a blockchain maintained by a peer-to-peer network. In most cryptocurrencies, transactions explicitly identify the previous transaction providing the fund...
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Article
Validation of a method to differentiate arterial and venous vessels in CT perfusion data using linear combinations of quantitative time-density curve characteristics
We aimed to develop and evaluate a new method that reliably differentiates between cerebral arteries and veins using voxel-wise CT-perfusion-derived parameters.
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Article
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