State transfer control of quantum systems on the Bloch sphere

The state transfer under control fields is analyzed based on the Bloch sphere representation of a single qubit. In order to achieve the target from an arbitrary initial state to a target state, the conditions that parameters should satisfy are deduced separately in two different requirements: One is in the case of the rotation angle around the x-axis being fixed and another is in the situation with a given evolution time. Several typical states trajectories are demonstrated by numerical simulations on the Bloch sphere. The relations between parameters and the trajectories are analyzed.     

<Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control for stochastic systems with Poisson jumps

This paper discusses the H _∞ control problem for a class of linear stochastic systems driven by both Brownian motion and Poisson jumps. The authors give the basic theory about stabilities for such systems, including internal stability and external stability, which enables to prove the bounded real lemma for the systems. By means of Riccati equations, infinite horizon linear stochastic state-feedback H _∞ control design is also extended to such systems.     

Mean-variance model based on filters of minimum spanning tree

This study aims to reduce the statistical uncertainty of the correlation coefficient matrix in the mean-variance model of Markowitz. A filtering algorithm based on minimum spanning tree (MST) is proposed. Daily data of the 30 stocks of the Hang Seng Index (HSI) and Dow Jones Index (DJI) from 2004 to 2009 are selected as the base dataset. The proposed algorithm is compared with the Markowitz method in terms of risk, reliability, and effective size of the portfolio. Results show that (1) although the predicted risk of portfolio built with the MST is slightly higher than that of Markowitz, the realized risk of MST filtering algorithm is much smaller; and (2) the reliability and the effective size of filtering algorithm based on MST is apparently better than that of the Markowitz portfolio. Therefore, conclusion is that filtering algorithm based on MST improves the mean-variance model of Markowitz.     

Hexagonal metric for linear codes over a finite field

This paper consider Hexagonal-metric codes over certain class of finite fields. The Hexagonal metric as defined by Huber is a non-trivial metric over certain classes of finite fields. Hexagonal-metric codes are applied in coded modulation scheme based on hexagonal-like signal constellations. Since the development of tight bounds for error correcting codes using new distance is a research problem, the purpose of this note is to generalize the Plotkin bound for linear codes over finite fields equipped with the Hexagonal metric. By means of a two-step method, the author presents a geometric method to construct finite signal constellations from quotient lattices associated to the rings of Eisenstein-Jacobi (EJ) integers and their prime ideals and thus naturally label the constellation points by elements of a finite field. The Plotkin bound is derived from simple computing on the geometric figure of a finite field.     

A note on the model reference adaptive control of linear parabolic systems with constant coefficients

The problem of constructing a model reference adaptive control law for an uncertain 1-dimensional parabolic system with one constant coefficient is considered in this paper. Adaptive control law are obtained by Lyapunov redesign method. The energy method for parabolic systems and the Agmon’s inequality are applied in the analysis, which leads to a stronger result than that of Hong and Bentsman (Automatica, 1994).     

Preventing rumor spreading on small-world networks

Since the spreading of harmful rumors can deeply endanger a society, it is valuable to investigate strategies that can efficiently prevent hazardous rumor propagation. To conduct this investigation, the authors modify the SIR model to describe rumor propagation on networks, and apply two major immunization strategies, namely, the random immunization and the targeted immunization to the rumor model on a small-world network. The authors find that when the average degree of the network is small, both two strategies are effective and when the average degree is large, neither strategy is efficient in preventing rumor propagation. In the latter case, the authors propose a new strategy by decreasing the credibility of the rumor and applying either the random or the targeted immunization at the same time. Numerical simulations indicate that this strategy is effective in preventing rumor spreading on the small-world network with large average degree.     

MULTIPLE CRITERIA DECISION MAKING： DISCORDANT PREFERENCES AND PROBLEM DESCRIPTION

There are many practical decision problems where decision makers＇ preferences may be inconsistent and contradictory. In this paper, new methods for ordering and classifying multi-attribute objects by discordant collective preferences are suggested. These methods are based on the theory of multiset metric spaces. The proposed techniques are applied to ranking companies and a competitive selection of projects, which are estimated by several experts upon multiple qualitative criteria.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

A FRAMEWORK FOR REAL-VALUED CIPHER SYSTEMS

Most cipher systems designed thus far are binary-valued or integer-valued cipher systems. Their security relies on the assumption that one-way functions exist. Though the existence of one-way functions has not been proved yet, most cryptographic researchers believe that one-way functions exist. In addition, many candidates for one-way functions have been proposed. Therefore, the key step for developing real-valued cipher systems is to define real one-way functions and to propose candidates for them. In this paper, based on computational complexity theory over the real field, we give two definitions of real one-way functions; one is for digital one-way functions and the other is for general one-way functions. Candidates for these two classes of one-way functions are also proposed. Moreover, we present two examples to demonstrate that the candidates for both digital one-way functions and general one-way functions can be applied to construct secure real-valued cipher systems.     

Revitalizing the Public Sphere: The Current System of Discourse and the Need for the Participative Design of Social Action

Public discourse in Western democracies, particularly in the United States, is far from the Habermasian ideal of citizens engaging in a rational discussion of public affairs. Rather than providing an arena for informed deliberation, the growing expertise of the media, lobbyists, and politicians has sub-optimized the current system of discourse to focus on emotional manipulation and the creation of polarized interests, each competing with each other for dominance. Avoiding a potentially disastrous outcome from this unbalancing of public discourse requires a revitalization of the public sphere and a return of the citizen voice in public decision making. To that end, systems thinkers have a tremendous opportunity and can play an important role. This article will explore the current challenges facing public discourse and outline that potential role.