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2021 ◽  
Vol 18 (12) ◽  
Author(s):  
Thomas Schüler ◽  
Petra Ganas ◽  
Marcel Fuhrmann ◽  
Miguel de Alba Aparicio ◽  
Estibaliz Lopez de Abechuco ◽  
...  
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2021 ◽  
Author(s):  
Paula M. Jacobs ◽  
James L. Tatum ◽  
Joseph D. Kalen ◽  
Lilia V. Ileva ◽  
Lisa A. Riffle ◽  
...  

2021 ◽  
Author(s):  
Mark Piper ◽  
Gregory Tucker ◽  
Irina Overeem ◽  
Albert Kettner ◽  
Eric Hutton ◽  
...  
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2021 ◽  
pp. 354-361
Author(s):  
Dewan M. Sarwar ◽  
David P. Nickerson
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2020 ◽  
Vol 26 (6) ◽  
pp. 1599-1617 ◽  
Author(s):  
Michael Leyer ◽  
Deniz Iren ◽  
Banu Aysolmaz

PurposeIdentifying handovers is an important but difficult to achieve goal for companies as handovers have advantages allowing for specialisation in processes as well as disadvantages by creating erroneous interfaces.Design/methodology/approachConceptualisation of a method based on theory and evaluation with company data using a process model repository.FindingsThe method allows to evaluate handovers from the perspective of roles in processes and grouping of employees in organisational units. It uses existing process model repositories connected with organisational chart information in companies to determine the density of handovers. The method is successfully evaluated using the example of a major telecommunications company with 1,010 process models in its repository.Practical implicationsCompanies can determine on various levels, up to the overall organisational level, in which parts of the company efforts are best spent to manage handovers in an optimal way.Originality/valueThis paper is first in showing how handovers can be conceptualised and identified with a large-scale method.


Author(s):  
Sergey N. Makarov ◽  
William A. Wartman ◽  
Mohammad Daneshzand ◽  
Kyoko Fujimoto ◽  
Tommi Raij ◽  
...  

AbstractBackgroundTranscranial magnetic stimulation (TMS) is currently the only non-invasive neurostimulation modality that enables painless and safe supra-threshold stimulation by employing electromagnetic induction to efficiently penetrate the skull. Accurate, fast, and high resolution modeling of the electric fields (E-fields) may significantly improve individualized targeting and dosing of TMS and therefore enhance the efficiency of existing clinical protocols as well as help establish new application domains.ObjectiveTo present and disseminate our TMS modeling software toolkit, including several new algorithmic developments, and to apply this software to realistic TMS modeling scenarios given a high-resolution model of the human head including cortical geometry and an accurate coil model.MethodThe recently developed charge-based boundary element fast multipole method (BEM-FMM) is employed as an alternative to the 1st order finite element method (FEM) most commonly used today. The BEM-FMM approach provides high accuracy and unconstrained field resolution close to and across cortical interfaces. Here, the previously proposed BEM-FMM algorithm has been improved in several novel ways.Results and ConclusionsThe improvements resulted in a threefold increase in computational speed while maintaining the same solution accuracy. The computational code based on the MATLAB® platform is made available to all interested researchers, along with a coil model repository and examples to create custom coils, head model repository, and supporting documentation. The presented software toolkit may be useful for post-hoc analyses of navigated TMS data using high-resolution subject-specific head models as well as accurate and fast modeling for the purposes of TMS coil/hardware development.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Dewan M. Sarwar ◽  
Reza Kalbasi ◽  
John H. Gennari ◽  
Brian E. Carlson ◽  
Maxwell L. Neal ◽  
...  

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