Extending the relational model to deal with probabilistic data

According to the soundness and completeness of information in databases,the expressive form and the semantics of incomplete information are discussed in this paper.On the basis of the discussion,the current studies on incomplete data in relational databases are reviewed.In order to represent stochastic uncertainty in most general sense in the real world,probabilistic data are introduced into relational databases.An extended relational data model is presented to express and manipulate probabilistic data and the operations in relational algebra based on the extended model are defined in this paper.     

A survey of uncertain data management

Uncertain data are data with uncertainty information,which exist widely in database applications.In recent years,uncertainty in data has brought challenges in almost all database management areas such as data modeling,query representation,query processing,and data mining.There is no doubt that uncertain data management has become a hot research topic in the field of data management.In this study,we explore problems in managing uncertain data,present state-of-the-art solutions,and provide future research directions in this area.The discussed uncertain data management techniques include data modeling,query processing,and data mining in uncertain data in the forms of relational,XML,graph,and stream.     

Updating Recursive XML Views of Relations

This paper investigates the view update problem for XML views published from relational data.We consider XML views defined in terms of mappings directed by possibly reeursive DTDs compressed into DAGs and stored in relations. We provide new techniques to efficiently support XML view updates specified in terms of XPath expressions with recursion and complex filters.The interaction between XPath recursion and DAG compression of XML views makes the analysis of the XML view update problem rather intriguing.Furthermore,many issues are still open even for relational view updates, and need to be explored.In response to these,on the XML side,we revise the notion of side effects and update semantics based on the semantics of XML views,and present efficient algorithms to translate XML updates to relational view updates. On the relational side,we propose a mild condition on SPJ views,and show that under this condition the analysis of deletions on relational views becomes PTIME while the insertion analysis is NP-complete.We develop an efficient algorithm to process relational view deletions,and a heuristic algorithm to handle view insertions.Finally,we present an experimental study to verify the effectiveness of our techniques.     

Scientific articles recommendation with topic regression and relational matrix factorization

In this paper we study the problem of recommending scientific articles to users in an online community with a new perspective of considering topic regression modeling and articles relational structure analysis simultaneously. First, we present a novel topic regression model, the topic regression matrix factorization （tr-MF）, to solve the problem. The main idea of tr-MF lies in extending the matrix factorization with a probabilistic topic modeling. In particular, tr-MF introduces a regression model to regularize user factors through probabilistic topic modeling under the basic hypothesis that users share similar preferences if they rate similar sets of items. Consequently, tr-MF provides interpretable latent factors for users and items, and makes accurate predictions for community users. To incorporate the relational structure into the framework of tr-MF, we introduce relational matrix factorization. Through combining tr-MF with the relational matrix femtorization, we propose the topic regression collective matrix factorization （tr-CMF） model. In addition, we also present the collaborative topic regression model with relational matrix factorization （CTR-RMF） model, which combines the existing collaborative topic regression （CTR） model and relational matrix factorization （RMF）. From this point of view, CTR-RMF can be considered as an appropriate baseline for tr-CMF. Further, we demonstrate the efficacy of the proposed models on a large subset of the data from CiteULike, a bibliography sharing service dataset. The proposed models outperform the state-of-the-art matrix factorization models with a significant margin. Specifically, the proposed models are effective in making predictions for users with only few ratings or even no ratings, and support tasks that are specific to a certain field, neither of which has been addressed in the existing literature.     

A Survey of the Rule Language RL/1

In this paper we introduced the RL project which aims to integrate logic programming,relational databases and constraint solving in a single relational framework.We gave a summary of the architecture of the RL/1 system and shorth discussed the characteristics of the RL/1 language.A target of the project has become to turn the RL/1 system into an industrial strength database interface.     

基于进程代数的安全协议分析与验证

Process algebra is the theories for concurrency.Now the methods based on process algebra for the analysis and verification of security protocols becomes one of the important methods for the study of the security protocols.In the paper,we outline these methods,especially the symbolic trace analysis method the bisimulation method.     

Regional pole assignment for uncertain delta-operator systems

The pole assignment in a specified disk by state feedback for uncertain delta-operator systems is studied. By making use of algebra Riccati equations, a sufficient and necessary condition of pole assignment for a kind of parameter uncertain delta-operator system in a specified disk by state feedback is presented. And the design method of state feedback controller is also developed.The proposed method can unify some previous rehted results of continuous and discrete time systems into the delta framework. The efficiency of the design method is illustrated by a numerical example.     

Robust stabilization of stochastic systems based on the LQ controller

The robust exponential stability in mean square for a class of linear stochastic uncertain control systems is dealt with. For the uncertain stochastic systems, we have designed an optimal controller which guarantees the exponential stability of the system. Actually, we employed Lyapunov fimction approach and the stochastic algebraic Riccati equation (SARE) to have shown the robusmess of the linear quadratic(LQ) optimal control law.And the algebraic criteria for the exponential stability on the linear stochastic uncertain closed-loop systems are given.     

A New Approach to Database Auto-Design by Logic

The database auto-design is an important problem in database research.In this paper we propose some new ideas and an approach called “logic approach” to implement the database auto-design.Given a relational scheme and a set of the functional dependencies for the relation we can obtain all of the functional dependencies and key for the relation and determine the normal form the relation satisfies.     

The output feedback control for uncertain nonholonomic systems

This paper considers the problems of almost asymptotic stabilization and global asymptotic regulation （GAR） by output feedback for a class of uncertain nonholonomic systems. By combining the nonsmooth change of coordinates and output feedback domination design together, we construct a simple linear time-varying output feedback controller, which can universally stabilize a whole family of uncertain nonholonomic systems. The simulation demonstrates the effectiveness of the proposed controller.     

Syntax theory of finite lattice-valued propositional logic

In this paper,we establish the graded syntax theory of lattice-valued propositional logic based on finite lattice implication algebras,define the notions of syntactic consequence operation and formal proof,and develop a kind of graded finite lattice-valued propositional calculus.By generalizing classic provable equivalence relation,we present a kind of generalized provable equivalence relation,and establish the corresponding quotient algebra.Finally,we establish the generalized deduction theorem by syntactic consequence operation,and establish the completeness in Pavelka’s sense based on finite chains.     

Processing Polynomial Algebraic Problems by Using SAC-2/ALDES

This paper discusses the portability of SAC-2/ALDES and reviews some applications in polynomial algebra.Furthermore,we indicate that the concept of the safety variable in the SAC-2/ALDES is not proper.When,for example,we used safety variable in isolating complex roots of polynomials,something wrong happened.     

粗糙蕴涵

Rough implication operator is the emphasis and difficulty in the study of rough logic. Due to the shortage of rough implication in [3]～[5], we redefine rough set and rough implication operator by Stone algebra, and introduce new rough operators such as rough intersection, rough union, and rough complement. Moreover the characteristics of the proposed rough implication are investigated ,and we also point out that the proposed implication operation is superior to that of three-valued Lukasiewicz logic.     

Encoding of primary structures of biological macromolecules within a data mining perspective

An encoding method has a direct effect on the quality and the representation of the discovered knowledge in data mining systems. Biological macromolecules are encoded by strings of characters, called primary structures. Knowing that data mining systems usually use relational tables to encode data, we have then to reencode these strings and transform them into relational tables. In this paper, we do a comparative study of the existing static encoding methods, that are based on the Biologist know-how, and our new dynamic encoding one, that is based on the construction of Discriminant and Minimal Substrings (DMS). Different classification methods are used to do this study. The experimental results show that our dynamic encoding method is more efficient than the static ones, to encode biological macromolecules within a data mining perspective.     

Nondeterministic Probabilistic Petri Net — A New Method to Study Qualitative and Quantitative Behaviors of System

There are many variants of Petri net at present,and some of them can be used to model system with both function and performance specification,such as stochastic Petri net,generalized stochastic Petri net and probabilistic Petri net.In this paper,we utilize extended Petri net to address the issue of modeling and verifying system with probability and nondeterminism besides function aspects.Using probabilistic Petri net as reference,we propose a new mixed model NPPN(Nondeterministic Probabilistic Petri Net) system,which can model and verify systems with qualitative and quantitative behaviours.Then we develop a kind of process algebra for NPPN system to interpret its algebraic semantics,and an actionbased PCTL(Probabilistic Computation Tree Logic) to interpret its logical semantics.Afterwards we present the rules for compositional operation of NPPN system based on NPPN system process algebra,and the model checking algorithm based on the action-based PCTL.In order to put the NPPN system into practice,we develop a friendly and visual tool for modeling,analyzing,simulating,and verifying NPPN system using action-based PCTL.The usefulness and effectiveness of the NPPN system are illustrated by modeling and model checking an elaborate model of travel arrangements workflow.     

Adaptive robust simultaneous stabilization of multiple n-degree-of-freedom robot systems

In this paper, the adaptive robust simultaneous stabilization problem of uncertain multiple n-degree-of-freedom (n-DOF) robot systems is studied using the Hamiltonian function method, and the corresponding adaptive L2 controller is designed. First, we investigate the adaptive simultaneous stabilization problem of uncertain multiple n-DOF robot systems without external disturbance. Namely, the single uncertain n-DOF robot system is transformed into an equivalent Hamiltonian form using the unified partial derivative operator (UP-DO) and potential energy shaping method, and then a high dimensional Hamiltonian system for multiple uncertain robot systems is obtained by applying augmented dimension technology, and a single output feedback controller is designed to ensure the simultaneous stabilization for the higher dimensional Hamiltonian system. On this basis, we further study the adaptive robust simultaneous stabilization control problem for the uncertain multiple n-DOF robot systems with external disturbances, and design an adaptive robust simultaneous stabilization controller. Finally, the simulation results show that the adaptive robust simultaneous stabilization controller designed in this paper is very effective in stabilizing multi-robot systems at the same time.     

Practical stabilization of a class of uncertain time-varying nonlinear delay systems

In this paper we deal with a class of uncertain time-varying nonlinear systems with a state delay. Under some assumptions, we construct some stabilizing continuous feedback, i.e. linear and nonlinear in the state, which can guarantee global uniform exponential stability and global uniform practical convergence of the considered system. The quadratic Lyapunov function for the nominal stable system is used as a Lyapunov candidate function for the global system. The results developed in this note are applicable to a class of dynamical systems with uncertain time-delay. Our result is illustrated by a numerical example.     

Isomorphic transformations of uncertainties for incorporating EMYCIN-style and PROSPECTOR-style systems into a distributed expert system

In the past,expert systems exploited mainly the EMYCIN model and the PROSPECTOR mdoel to deal with uncertaintes.In other words,a lot of stand-alone expert systems which use thse two models are available.If we can use the Internet to Couple them together,their performance will be improved through cooperation.This is because the problem-solving ability of expert systems is greatly improved by the way of cooperation among different expert systems in a distributed expert system.Cooperation between different expert systems with these two heterogeneous uncertain reasoning models is essentially based on the transformations of uncertainties of propositions between these two models.In this paper,we discovered the exactly isomorphic transformations uncertaintis between uncertain reasoning models,as used by EMYCIN and PROSPECTOR.     

An orthogonal basis for the hyperbolic hybrid polynomial space

Motivated by the wide usage of the Tchebyshev basis and Legendre basis in the algebra polynomial space, we construct an orthogonal basis with the properties of the H-Bézier basis in the hyperbolic hybrid polynomial space, which is similar to the Legendre basis and holds remarkable properties. Moreover, we derive the transformation matrices that map the H-Bézier basis and the orthogonal basis forms into each other. An example for approximating the degree reduction of the H- Bézier curves is sketched to illustrate the utility of the orthogonal basis.     

On Robust H2 Estimation

The problem of state estimation for uncertain systems has attracted a recurring interest in the past decade. In this paper, we shall give an overview on some of the recent development in the area by focusing on the robust H2 (Kalman) filtering of uncertain discrete-time systems. The robust H2 estimation is concerned with the design of a fixed estimator for a family of plants under consideration such that the estimation error covariance is of a minimal upper bound. The uncertainty under consideration includes norm-bounded uncertainty and polytopic uncertainty. In the finite horizon case, we shall discuss a parameterized difference Riccati equation approach for systems with norm-bounded uncertainty and pinpoint the difference of state estimation between systems without uncertainty and those with uncertainty. In the infinite horizon case, we shall deal with both the norm-bounded and polytopic uncertainties using a linear matrix inequality (LMI) approach. In particular, we shall demonstrate how the conservatism of design can be improved using a slack variable technique. We also propose an iterative algorithm to refine a designed estimator. An example will be given to compare estimators designed using various techniques.