Controlled remote implementation of quantum operations with high-dimensional systems

We present two protocols for the controlled remote implementation of quantum operations between three-party high-dimensional systems. Firstly, the controlled teleportation of an arbitrary unitary operation by bidirectional quantum state teleportaion （BQST） with high-dimensional systems is considered. Then, instead of using the BQST method, a protocol for controlled remote implementation of partially unknown operations belonging to some restricted sets in high-dimensional systems is proposed. It is shown that, in these protocols, if and only if the controller would like to help the sender with the remote operations, the controlled remote implementation of quantum operations for high-dimensional systems can be completed.

Implementation of National Tuberculosis Control Pro-gramme (Focus on Registration, Case-Management and Treatment).

The results of three nationwide epidemiological surveys on tuberculosis showed the declination of the magnitude of tuberculosis from 1979 to 1990 was slower. The case registration rates and new case registration rates within ten years

A framework to develop and test a model-free motion control system for a forestry crane

This article has the objective of presenting our method to develop and test a motion control system for a heavy-duty hydraulically actuated manipulator,which is part of a newly developed prototype featuring a fully-autonomous unmanned forestry machine.This control algorithm is based on functional analysis and differential algebra,under the concepts of a new type of approach known as model-free intelligent PID control(iPID).As it can be unsafe to test this form of control directly on real hardware,our main contribution is to introduce a framework for developing and testing control software.This framework incorporates a desktop-size mockup crane equipped with comparable hardware as the real one,which we design and manufactured using 3D-printing.This downscaled mechatronic system allows to safely test the implementation of control software in real-time hardware directly on our desks,prior to the actual testing on the real machine.The results demonstrate that this development framework is useful to safely test control software for heavy-duty systems,and it helped us present the first experiments with the world’s first unmanned forestry machine capable of performing fully autonomous forestry tasks.

SCM Implementation Decisions Under Asymmetric Information: An Agency Approach

The optimization investment policy decision of SCM-supply chain management-implementation has been analysed under symmetric and asymmetric information conditions.For both conditions,SCM implementation optional decision optimizing models have been developed.In these models,both clients and vendors try to pursue their own benefits.Based upon the principal-agent theory,the models show to what extent a principal(a client)needs to pay more to an agent(a vendor)in a context of asymmetric information.For the client it is important to understand the extra costs to be able to adopt effective strategies to stimulate a vendor to perform an optimal implementation of a SCM system.The results of a simulation experiment regarding SCM implementation options illustrate and verify the theoretical findings and confirm the general notion that the less informed party is obliged to pay information rent to the better-informed party.

A Wavelet Neural Network Based Non-linear Model Predictive Controller for a Multi-variable Coupled Tank System

In this paper, a novel real time non-linear model predictive controller(NMPC) for a multi-variable coupled tank system(CTS) is designed. CTSs are highly non-linear and can be found in many industrial process applications. The involvement of multi-input multi-output(MIMO) system makes the design of an effective controller a challenging task. MIMO systems have inherent couplings,interactions in-between the process input-output variables and generally have an complex internal structure. The aim of this paper is to design, simulate, and implement a novel real time constrained NMPC for a multi-variable CTS with the aid of intelligent system techniques. There are two major formidable challenges hindering the success of the implementation of a NMPC strategy in the MIMO case. The first is the difficulty of obtaining a good non-linear model by training a non-convex complex network to avoid being trapped in a local minimum solution. The second is the online real time optimisation(RTO) of the manipulated variable at every sampling time.A novel wavelet neural network(WNN) with high predicting precision and time-frequency localisation characteristic was selected for an MIMO model and a fast stochastic wavelet gradient algorithm was used for initial training of the network. Furthermore, a genetic algorithm was used to obtain the optimised parameters of the WNN as well as the RTO during the NMPC strategy. The proposed strategy performed well in both simulation and real time on an MIMO CTS. The results indicated that WNN provided better trajectory regulation with less mean-squared-error and average control energy compared to an artificial neural network. It is also shown that the WNN is more robust during abnormal operating conditions.