An efficient privacy-preserving blockchain storage method for internet of things environment.

Blockchain is a key technology to realize decentralized trust management. In recent studies, sharding-based blockchain models are proposed and applied to the resource-constrained Internet of Things (IoT) scenario, and machine learning-based models are presented to improve the query efficiency of the sharding-based blockchains by classifying hot data and storing them locally. However, in some scenarios, these presented blockchain models cannot be deployed because the block features used as input in the learning method are privacy.

Determination of the Three-Dimensional Rate of Cancer Cell Rotation in an Optically-Induced Electrokinetics Chip Using an Optical Flow Algorithm.

Our group has reported that Melan-A cells and lymphocytes undergo self-rotation in a homogeneous AC electric field, and found that the rotation velocity of these cells is a key indicator to characterize their physical properties. However, the determination of the rotation properties of a cell by human eyes is both gruesome and time consuming, and not always accurate. In this paper, a method is presented to more accurately determine the 3D cell rotation velocity and axis from a 2D image sequence captured by a single camera.