Improving Authenticated Dynamic Dictionaries, with Applications to Cryptocurrencies

We improve the design and implementation of two-party and three-party authenticated dynamic dictionaries and apply these dictionaries to cryptocurrency ledgers. A public ledger (blockchain) in a cryptocurrency needs to be easily verifiable. However, maintaining a data structure of all account balances, in order to verify whether a transaction is valid, can be quite burdensome: a verifier who does not have the large amount of RAM required for the data structure will perform slowly because of the need to continually access secondary storage. We demonstrate experimentally that authenticated dynamic dictionaries can considerably reduce verifier load. On the other hand, per-transaction proofs generated by authenticated dictionaries increase the size of the blockchain, which motivates us to find a solution with most compact proofs. Our improvements to the design of authenticated dictionaries reduce proof size and speed up verification by 1.4-2.5 times, making them better suited for the cryptocurrency application. We further show that proofs for multiple transactions in a single block can compressed together, reducing their total length by approximately an additional factor of 2. We simulate blockchain verification, and show that our verifier can be about 20 times faster than a disk-bound verifier under a realistic transaction load

Scheduling in MRI scans processing

In this chapter we present a new approach to reduce the examination time of MRI systems. The time reduction is accomplished by dividing MRI scans into segments, which are intermixed to reduce the MRI examination time. The intermixing algorithms are based on a scheduling framework. First, the concept of multiple scan sets (ExamCards) is introduced. Then an explicit definition of the algorithms for different duty cycle limitations is presented. Next, the results of application of the algorithms to the Philips Healthcare routine examinations. Finally, the MRI experiments that employs this time reduction approach are described. These algorithms are robust with respect to MRI hardware changes, thus they can be utilized to improve overall evolvability of the MRI system