Abstract:Strictly synchronized SPNs (stochastic Petri nets) are very popular in stochastic Petri nets made up of sub-models. Because of the problem of state space’s explosion, performance analysis of strictly synchronized SPNs has not been solved completely. Formulas that show performance equivalence of four elementary subnets, which are sequence subnet, parallel subnet, choice subnet and iteration subnet, are presented. A decomposition approach called STED (synchronous transition equivalent decomposition) is proposed in this paper and can be applied to SPNs with one or more synchronous transitions, especially such models with isomorphic sub-models.

Abstract:The problem of constructing a Petri net feedback controller, which enforces the conjunction of a set of linear inequalities on the reachable marking of the plant modeled by Petri net, is discussed in this paper. A new net reduction──HMSNR (holding marking sum net reduction), is presented, which fuses all the constrained places into one place whose marking is equal to the sum of the markings of the constrained places. The net reduction eases design of controller and holds remarkable advantage especially for the systems with large scale. The method is proved to be simpler and more efficient than the method presented by Moody, et al., using an applied instance that is also used by Moody, et al.

Abstract:Internet-Based Web application systems are gradually built as software service coordination systems. In an open, dynamic and changeful application environment, trust is an important thing for security and reliability of software services and systems. In this paper, first an Agent-based software service coordination model is presented. Then a trust valuation model is given to value trust relationships between software services. Trust is abstracted as a function of subjective expectation and objective experience, and a reasonable method is provided to combine the direct experience and the indirect experience from others. In comparison with an other’s work, a complete trust valuation model is designed, and its reasonability and operability is emphasized. This model can be used in coordination and security decision between software services.

Abstract:Having the ability of handling complex transaction in heterogeneous environment, workflow is coming into notice in the area of science research, e-government, e-business, there are lots of research achievements and productions. Major parts of the studies are concentrated in the workflow scheduling, interface with database and legacy system, etc., few efforts are put into the researches of architecture, model and definition language of workflow management system. In this paper, workflow meta-model of WfMC is analyzed. According to real cases, extensions and modifications to workflow meta-model and workflow definition language are introduced, so as to satisfy the increasing variability of business process and application of new technologies.

Abstract:As a specification of middleware, real-time CORBA (common object request broker architecture) defines uniform CORBA priority which is independent of any operating system. The CORBA priority is carried with the CORBA invocation and is used to ensure that all threads subsequently executing on behalf of the invocation run at the appropriate native priority, which is mapped from that CORBA priority. How to map many CORBA priority levels to fewer native priority levels and maintain the order of these priorities is very important. The mapping problem is common in real-time middleware. The priority mapping mechanism of real-time CORBA is introduced briefly. The two methods of how to map middleware priority to native operating system priority are presented, the two methods are static mapping method and dynamic mapping method. Static mapping method is simple to be implemented, but it can break the interoperability, portability and the strict order of middleware’s priorities. Dynamic mapping method is complex to be implemented, but it can maintain the strict order of middleware’s priorities.

Abstract:Component based software engineering (CBSE) is one of the most effective solutions to improve software development quality and productivity. Component composition and compositional reasoning are the core technologies and frontier research areas in CBSE. Based on the characteristics of software components and inspired by process construction methods in process algebra, in this paper, six component composition mechanisms are proposed to integrate software components simply and conveniently. And it is argued to compose interfaces at the same time of component composition, consequently to generate more powerful and more abstract interfaces to support integration of coarse-grained components and raise the abstract level of component composition. Moreover, based on the Wright’s research on formal specification of software architecture, compositional reasoning algorithms about the behaviors of composite component as well as the protocols of composite interfaces are developed in this paper, which establish a foundation to analyze, validate, simulate composite systems.

Abstract:Super-Resolution restoration is a technique for estimating an unaliased high-resolution image (or a sequence) from an aliased video sequence and combating additive noise and blurring due to the finite detector size and optics. In this paper, an improved Bayesian MAP estimator with multi-scale edge-preserving regularization for super-resolution restoration is proposed. The confidence of the motion estimation result is validated to eliminate motion artifact. The wavelet representation of an image is utilized to define the spatial activity measure of the image, and further to construct a novel multi-scale Huber-Markov model. The experimental results show that the multi-scale Huber-Markov model can be incorporated into Bayesian MAP estimator to preserve the edges of the super-resolution image effectively. This proposed algorithm is widely used for remote sensing, medical imaging, high-definition television (HDTV) standard and creation of synthetic ‘video zoom’.

Abstract:It is very important to detect singularities (core and delta) accurately and reliably for classification and matching of fingerprints. In this paper, a method for singularity detection in fingerprint images is presented to improve accuracy of the position and reliability of the singularity. Firstly, the singularities are detected based on block images through shifting position of the whole image time after time at the same block size and the concentrative region of singularities detected under different positions is got and the centroid of the region is computed to gain the accurate position of singularities. Then, the reliability of singularities detected above is determined with multilevel block sizes. In this method, the characteristics of the relative concentration of the position of singularities detected through image shift and of the corresponding relationship of the singularities detected with multilevel block sizes are used and the singularities are detected accurately and reliably. Experimental results show that the method performs well and it is robust to poor quality images.

Abstract:The efficiency of data mining algorithms is strongly needed with data becoming larger and larger. Density-Based clustering analysis is one kind of clustering analysis methods that can discover clusters with arbitrary shape and is insensitive to noise data. In this paper, a new kind of clustering algorithm that is called CURD (clustering using references and density) is presented. The creativity of CURD is capturing the shape and extent of a cluster by references, and then analyzes the data based on the references. CURD keeps the ability of density based clustering method抯 good features, and it can reach high efficiency because of its linear time complexity, so it can be used in mining very large databases. Both theory analysis and experimental results confirm that CURD can discover clusters with arbitrary shape and is insensitive to noise data. In the meanwhile, its executing efficiency is much higher than traditional DBSCAN algorithm based on R*-tree.

Abstract:It is a very difficult problem in machine learning to learn uncertain knowledge automatically without prior domain knowledge. In this paper, a theory is developed to express, measure and process uncertain information and uncertain knowledge according to uncertainty measure of decision table and decision rule. Based on the Skowron’s default rule generation algorithm, a self-learning model and the method is developed to solve this problem. Simulation results illustrate the efficiency of this self-learning method.

Abstract:Automatic text categorization is an effective method to increase the efficiency and quality of information utilizing. The combination of a set of different classifiers can often achieve higher classification accuracy. The concept of full information matrix is first given, and then an integration method of multiple classifiers based on adaptive weight adjusting is presented in this paper. The classifiers and their weights are determined automatically and adaptively with this method. The effective integration of each classifier抯 result can be realized by analyzing the statistical information of the classifier on the training set. The classification performance is promoted by the improvement of the precision and the recall. The effectiveness of the method is shown by the text classification experiments on the Reuters-21578 text sets.

Abstract:Two improved Elman neural networks, output-input feedback Elman network and output-hidden feedback Elman network are presented based on the Elman neural network. By using the output-input feedback Elman network as a passageway of the error back propagation, a recurrent back propagation control neural network model is developed. The stability of the improved Elman neural networks is proved in the sense of Lyapunov stability theory. The optimal adaptive learning rates are obtained, which can guarantee the stable convergence of the improved Elman networks. The ultrasonic motor is simulated by using the Elman and improved Elman networks respectively. Besides simulating the speed of the ultrasonic motor successfully, some useful results are also obtained. According to the results, the different network models based on the sampling situation in the fieldwork can be chosen. Numerical results show that the recurrent back propagation control neural network controller has good effectiveness for various kinds of reference speeds of the ultrasonic motor.

Abstract:Anomaly Detection techniques assume all intrusive activities deviate from the norm. In this paper a new anomaly detection model is found to improve the veracity and efficiency. The proposed model inestablishes a normal activity profile of the systemcall sequences by using Genetic Programming. One instance of the model monitors one process. If the model finds the real systemcall sequences profile of the process deviating from the normal activity profile, it will flag the process as intrusive and take some actions to respond to it. And a new method of calculating the fitness and two operators to generate the next offspring are provided. According to the comparison with some of current models, the model is more veracious and more efficient.

Abstract:Architectures of servers have very important effects on their performance. Some shortcomings of the existing design of servers’ architectures are indicated and some design principals are presented in this paper. A new architecture of servers ‘pipeline’ and a design pattern ‘resource manager’ based on the above analysis are proposed in this paper. A real Web server is implemented by using these new techniques. The testing results show that it is much better than existing servers on performance.

Abstract:WAS (Web application server) is a distributed system which provides runtime integrated services for transactional Web applications. To improve the dependability and scalability of WASs, one effective way is to balance loads via adaptive load balancing service based on the middleware. The existing adaptive load balancing services, however, have inadequacies such as lack of server transparency and extensible load balancing strategy etc., and provide insufficient functionality to satisfy WASs. In this paper, the key requirements of adaptive load balancing services for WASs are addressed first, and then the design of a novel adaptive load balancing service is presented. The key design challenges including hot plug-in, customizable load balancing strategy, load feedback and adaptive control, state migration and fault tolerance etc. are described, and the technical solutions are outlined. Lastly, a comparative study with other related works is given The adaptive load balancing service is developed and implemented in WebFrame2.0 application server by using Java RMI.

Abstract:With the enormous growth of information on the Web, Internet has become one of the most important information sources. However, limited by the network bandwidth, users always suffer from long time waiting. Web pre-fetching is one of the most popular strategies, which are proposed for reducing the perceived access delay and improving the service quality of Web server (QoS). A semantics-based pre-fetching model is presented in this paper. This model predicts future requests based on latent intention that the user抯 current access path implies in semantics, rather than on the temporal relationships between URL accesses, which overcomes the limitation of previous pre-fetching approaches. The hidden Markov model (HMM) is employed for mining actual intention from access patterns. Experimental results show that the proposed pre-fetching model has better general performance.

Abstract:In this paper, a cryptographic protocol together with its cryptographic algorithms is regarded as one system, and a security model for the system is built. Based on assume-guarantee compositional reasoning techniques, a new assume-guarantee based reasoning rule and algorithm are proposed, and the soundness of the rule is proved. In realizing model checking to the cryptographic protocol system, several difficulties are solved chiefly such as decomposition of the system, generation of assumed functions, and specifying security properties in forms of both logic formulas and processes. Using this security model and assume-guarantee based reasoning techniques, the kerberos cryptographic protocol system is verified.

Abstract:In this paper, the issues of entity authentication and content authentication mechanism of the digital signature based on multimedia system are addressed. Based on the analysis of the security gap in the authentication mechanism using digital signature, a novel authentication protocol combining digital signature and fragile watermarking are proposed. Double entity authentication based on digital signature and content authentication base on fragile watermarking is achieved. Illegal access to system, edition, and forgery of multimedia document is proven to be impossible. According to the analysis, the security, creditability, and authenticity are achieved.

Abstract:The definition of robust threshold key escrow scheme (RTKES) is proposed in this paper. Namely, in RTKES, malice escrow agency fail to obtain the system secret key or user抯 secret key, even if the number of malice escrow agency is more than or equal to the value of threshold. Clearly, the problem of 搖ser抯 secret key completely depends on the trusted escrow agency?is solved if RTKES exists. In this paper, it is proved that the RTKES does exist, and some concrete designs of two classes of RTKES are given. In these schemes, the problem of 搊nce monitor, monitor for ever?is solved effectively, every escrow agency can verify correctness of the secret shadow that he escrows during secret shadow distribution and monitor agency can exactly decide which escrow agency forges or tampers secret shadow during monitor procedure. Since the proposed RTKES is also threshold key escrow scheme, when an escrow agency or few agencies is not cooperating, monitor agency can easily reconstruct session key to monitor as long as there are other k effective escrow agencies. In addition, it also resists against LEAF feedback attack.

Abstract:Digital fingerprinting has appeared as a new technique for copyright protection of digital contents. How to defense collusive attack is one of the key problems when designing fingerprinting algorithms. In this paper, based on the binary random coding methods, a fingerprinting algorithm and the corresponding tracing algorithm are proposed by using a pseudo-random sequence to control the embedding of the fingerprint bits. Both theoretical analysis and experimental results show that under reasonable collusion size, by the fingerprinting algorithm, the owner can trace the traitors quite efficiently and the probability to accuse an innocent buyer can be made as close as to 0. Furthermore, because the owner need not know the buyers?fingerprints, the method can serve as a good coding algorithm in the design of asymmetric fingerprinting schemes.

Abstract:Due to the MAC (medium access control) protocol, routing protocol and TCP itself, the TCP flow is very unstable in the wireless Ad Hoc networks based on IEEE802.11. However, the main reasons that make the TCP flow unstable are the unfairness of MAC protocol and the false link failure message that causes the long route discovery procedure. Combining with the IEEE802.11 MAC protocol and DSR routing protocol, these causes are analyzed in detail and the enhanced algorithm to IEEE802.11 MAC protocol and DSR routing protocol is given in this paper. The simulational results show that the proposed algorithm can ultimately avoid the instability of TCP flow and increase its average throughput in the wireless Ad Hoc networks.