Model predictive control (MPC) is a widely used control design method in the process industry. Its main advantage is that it allows the inclusion of constraints on the inputs and outputs. Usually MPC uses linear discrete-time models. We extend MPC to max-min-plus discrete event systems. In general the resulting optimization problems are nonlinear and nonconvex. However, if the state equations a...

BACKGROUND To investigate the infection status and predominant genotype distribution of human papillomavirus (HPV) infection among Chinese patients with mucopurulent cervicitis (MPC) or cervical cancer (CC) in Hangzhou. METHODS Initially, 217 cases of healthy cervix controls (n=50), acute MPC (n=89), and CC (n=78) were included; samples were collected between January 1, 2010, and January 30, ...

Model predictive control (MPC) is a design technique that solves (typically on-line) optimization problems to determine a suitable feedback action. It is widely used because of the capability to deal with constraints and MIMO systems [3]. To treat practical industrial processes with MPC, use of so called economic cost functionals are proposed and considered for optimization in [1]. In this sche...

Mass production is an important co mponent of any pest or vector control program that requires the release of large number of insects. As part of efforts to develop an area-wide program involving the sterile insect technique (SIT) for the control of mosquitoes, the Insect Pest Control Laboratory of the Food and Agriculture Organization-International Atomic Energy Agency (FAO-IAEA Joint Division...

A t-out-of-n secret-sharing scheme allows an honest dealer D to distribute a secret s among n players, such that any subset of t players has no information about s, but every set of t + 1 players can collaboratively reconstruct the secret. The most famous secret-sharing scheme is Shamir’s Sharing Scheme [Sha79] (cf. Section 7.1.2). It uses polynomials to obtain the desired properties. Before pr...

Most protocols for multi-party computation (MPC) are secure either against information-theoretic (IT) or against computationally bounded adversaries. Hybrid-secure MPC protocols guarantee different levels of security, depending on the power of the adversary. We present a hybrid-secure MPC protocol that provides an optimal trade-off between IT robustness and computational privacy: For any robust...

The Modular Program Constructor (MPC) is an open-source Java based utility, built upon JSim's Mathematical Modeling Language (MML) ( http://www.physiome.org/jsim/) that uses directives embedded in model code to construct larger, more complicated models quickly and with less error than manually combining models. A major obstacle in writing complex programs for modeling physiological processes is...

The application of the I band Tully–Fisher relation towards determining the Hubble constant is reviewed, with particular attention to the impact of scatter and bias corrections in the relation. A template relation is derived from galaxies in 24 clusters. A subset of 14 clusters with cz ∼ 4000 to 9000 km s is used as an inertial frame to define the velocity zero point of the relation. Twelve gal...

The paper presents a new parallel language, mpC, designed specially for programming high-performance computations on heterogeneous networks of computers, as well as its supportive programming environment. The main idea underlying mpC is that an mpC application explicitly defines an abstract network and distributes data, computations and communications over the network. The mpC programming envir...

Most approaches of chance–constrained robust MPC utilise an open– loop model for uncertainty prediction; this results in conservative control. To avoid this some approaches propose robust MPC (RMPC) based on closed–loop prediction, and these often give improved dynamic performance at a small expense to constraint handling performance. The aim of this paper is to extend the methodology of (Warre...