RZcoin: Ethereum-Based Decentralized Payment with Optional Privacy Service

As the blockchain 2.0 platform, Ethereum’s turing complete programming language and smart contract components make it play an important role in the commercialization of blockchain. With the further development of blockchain applications, the privacy and security issues of Ethereum have gradually emerged. To solve this problem, we proposed a blockchain privacy protection model called RZcash in the previous work. It implements the dynamically updateable and verifiable hiding of the asset information in Ethereum, namely the account balance and transaction amount. However, RZcash does not pay attention to the key redundancy problem that may be caused by the creation of secret accounts. In addition, the large size of proofs gives it high communication costs. In response to these problems, we further improve RZcash. For the key redundancy problem, we construct a new signature scheme based on the ciphertext equivalent test commitment. Moreover, we use the Schnorr signature and bulletproof to improve the corresponding proof scheme in RZcash, thereby reducing the size of proof. Based on these improvements, we propose a decentralized payment system, called RZcoin, based on Ethereum. Finally, we implement the algorithm model of RZcoin and evaluate its security and performance. The results show that RZcoin has higher security and Lower communication cost than RZcash.

A multi-model control of nonlinear systems: A cascade decoupled design procedure based on stability and performance

Recently, the multi-model controllers design was proposed in the literature based on integrating of the stability and performance criteria. Although these methods overcome the redundancy problem, the decomposition step is very complex and time consuming. In this paper, a cascade design of multi-model control is presented that is made from two sequential steps. In the first step, the nonlinear system is decomposed into a set of linear subsystems by just considering the stability criterion. In this step, the gap metric is used as a smart tool to measure the distance between linear subsystems. While the closed-loop stability is gained through the first step, the performance is improved in the second step by adding internal model controllers in a cascade structure. Therefore, the proposed idea supports designing a multi-model controller in a simple way by integrating the stability and performance criteria in two independent cascade steps. As a result, the proposed method avoids the model redundancy problem, has a simple structure, guarantees the robust stability, and improves the performance. Two nonlinear chemical processes are simulated to evaluate the proposed multi-model controller approach.

Forward Static Optimization in Dynamic Simulation of Human Musculoskeletal Systems: A Proof-of-Concept Study

Static optimization (SO) has been used extensively to solve the muscle redundancy problem in inverse dynamics (ID). The major advantage of this approach over other techniques is the computational efficiency. This study discusses the possibility of applying SO in forward dynamics (FD) musculoskeletal simulations. The proposed approach, which is entitled forward static optimization (FSO), solves the muscle redundancy problem at each FSO time step while tracking desired kinematic trajectories. Two examples are showcased as proof of concept, for which results of both dynamic optimization (DO) and FSO are presented for comparison. The computational costs are also detailed for comparison. In terms of simulation time and quality of muscle activation prediction, FSO is found to be a suitable method for solving forward dynamic musculoskeletal simulations.