Revealing Structural Information about Complex Systems from Minimal Data

Possibilities for transfer of relevant data without revealing structural information

In this paper, we discuss how we safely exchanged proprietary data between third parties in the early years of predictive ADME/Tox model development. At that time, industry scientists wanted to evaluate predictive models, but were not willing to share their structures with software vendors. At the same time, model developers were willing to run the scientists' structures through their models, b...

Structural Properties of Multirate Sampled-Data Systems

The application of Networked Control Systems (NCS) in which sensory and control signals are transmitted via shared data communication networks, is growing significantly and these systems have been the subject of research during the last decade. On the other hand, multirate sampled data systems have been investigated since a long time. In this paper, conditions under which a networked control sy...

Mining Minimal Constrained Flow Cycles from Complex Transaction Data

Transaction data in domains such as trading records from online financial or other markets, logistics delivery registers, and many others, are being accumulated at an increasing rate. In this type of data each transaction has a complex format, being usually associated with attributes such as time, numerical quantity, parties involved, and so on. Performing data mining on trace record data of co...

Intersubject information mapping: revealing canonical representations of complex natural stimuli

Real-world time-continuous stimuli such as video promise greater naturalism for studies of brain function. However, modeling the stimulus variation is challenging and introduces a bias in favor of particular descriptive dimensions. Alternatively, we can look for brain regions whose signal is correlated between subjects, essentially using one subject to model another. Intersubject correlation ma...

Thinking Systemically About Complex Systems