Abstract:On the basis of intensive study of the problem frames (PF) approach, this paper extracts and develops an ontology for conceptualizing the requirements model of the PF approach and designs an ontology-guided modeling process. The aim is to present the analysts with a modeling guide and with standard the modeling activities. Finally, a case study has been given to illustrate the whole process.

Abstract:QVT (Query/View/Transformation) Relations cannot describe the pattern that includes other patterns, so it has some difficulties in defining the rules of a process model transformation. To solve this problem, the paper extends QVT Relations with three new concepts: Pattern Factor, Nested Relation Expression, and Relationship End Constraint. The paper also discusses the pattern matching and the model creating semantics after the extension. At Last, a case study is presented to show how the extension could deal with process model transformations.

Abstract:A propositional projection temporal logic (PPTL) based model checking approach for rate monotonic scheduling (RMS) is presented. With this approach, RMS controlled systems are modeled by PROMELA, which is the system modeling language in model checker SPIN. The desired property is specified by a PPTL formula. Next, whether or not the system satisfies the property can be verified with SPIN. Accordingly, the schedulability of a group of tasks can be obtained; meanwhile, other properties of the tasks scheduling system under RMS algorithm can also be verified.

Abstract:This paper proposes a semantic role labeling (SRL) approach for the Chinese, based on feature combination and support vector machine (SVM). The approach takes the constituent as the labeling unit. First, this paper defines the basic feature set by selecting the high-performance features of existing parsing-based SRL systems. Then, a statistics-based method is proposed to construct a combined feature set derived from the basic feature set. According to the distribution of combining features in both positive and negative instances, the ratio of between-class to within-class distance is utilized as the measurement of classifying the performance the feature, and then choosing the combining features with high ratios into the combining feature set. Finally, the experimental results show that the feature combination method-based SRL achieved 91.81% F-score on Chinese PropBank (CPB) corpus, nearly 2% higher than the traditional method.

Abstract:This paper presents a two-stage pronoun resolution algorithm. It does not need to clean the testing corpus and predefine patterns manually. In the first stage of the algorithm, some new features and machine learning methods are used to classify pronouns into anaphoric and non-anaphoric ones. In the second stage, these two kinds of pronouns are resolved respectively. For the anaphoric ones, some methods are presented to extract distance, syntactic, and semantic features etc. For the non-anaphoric ones, the Right Frontier Rule is improved to do the resolution work. While testing the corpus published by Byron in 2004, this algorithm achieves a precision of 77.0% and a recall of 66.0%. Compared with the work of Byron, the algorithm is fully automatic, and the results are much better.

Abstract:This paper analyzed various existing approaches of structural grammar parsing, and addressed the problem of over-classification and under-classification. Then a hierarchically classified phase structure grammar (HC-PSG) and a hierarchically classified probabilistic context-free grammar (HC-PCFG) parsing are proposed to respond to this challenge. A measure of class clustering is designed to eliminate the classification ambiguity of grammar rules. The HC approach implements a general learning rule from a small number of phrase instances. An instant clustering method is used to disambiguate rules learned from corpus. The HC method is also extended to context sensitive grammar parsing to improve performance. It employs the classification of the context relevancy to handle the problem of corpus sparsity. By all the means, it can leverage the conflicts between under-classification and over-classification.

Abstract:This paper presents a series of models and algorithms to implement OLAPing on graph data. The major contributions include (1) proposing a graph-oriented data warehouse model, called a double star model, (2) proposing the concept of graph data cube and its building algorithm, (3) designing an informational OLAPing algorithm, I-OLAPing, (4) designing topological dimensional OLAPing algorithm, T-OLAPing, and (5) building a Graph OLAPing prototype, Graph OLAPer1.0, based on the proposed approaches. Experimental results show that the Graph OLAPing algorithms designed and implemented in this paper, together with Graph OLAPing prototype, Graph OLAPer1.0 can work effectively on Co-Author Networks.

Abstract:This paper aims at explaining the cross-border topological join queries of spatial fragments of the zone fragmentation data in distributed spatial database (DSDB), and the optimizing methods for such queries are proposed. First, the fragmentation and distribution of spatial data in a distributed environment are discussed, and the extra principles for spatial data fragmentation are put forward, including spatial clustering, non-partitioning on spatial objects, and maintaining logical seamless. Then, the fragment joins in zone fragmentation are classified into two categories: cross-border join and non-cross-border join; the topological relationships are also classified into two categories. Thus, the emphasis is put on the two types of cross-border topological joins. Two theorems for cross-border topological join optimization are proposed and proved. Based on the theorems, the optimizing rules for cross-border spatial topological join are given, including the removing rules and the transforming rules of fragment joins. Finally, tests are designed to compare three join strategies that include Na?ve join strategy, semi-join strategy and the proposed strategies. The results show that the proposed methods greatly improve the cross-border join optimizing efficiency. Therefore, the theorems and methods proposed in this work can be applied to the optimization of distributed cross-border spatial topological queries.

Abstract:This study provides models to analyze the intervention over uncertain data. The main contributions include: (1) It establishes a base model named Uncertain Surveillance; (2) It proposes probabilistic intervention strategies over uncertain surveillance with evaluating algorithms; (3) It gives extensive experiments and makes comparisons to show that the proposed model is highly precise and efficient in three order magnitudes of na?ve methods.

Abstract:A distributed sensing algorithm is proposed which considers the nodes’ contention relation and the sensing cost. The algorithm is based on the distributed minimum clique partition, which can classify nodes into several cliques. Then, the optimal spectrum sensing scheme for each node is calculated on the foundation of cliques. The computation complexity is O(N²+M×N), N is the node number of the network, and M is the number of channels. By a detailed simulation, the results demonstrate that the network performance is improved efficiently with the use of the algorithm.

Abstract:This paper considers the time hopping impulse radio ultra wide band (TH-IR UWB) sensor networks, with n sensor nodes uniformly and independently located on a square and a Sink. The upper bounds on the lifetime of ordinary clustering dense and extended TH-IR UWB sensor networks are derived respectively. For ordinary clustering networks, the cluster head aggregates data from the nodes within its own cluster, and relays data to other cluster heads. The results indicate that the upper bounds on the lifetime of ordinary clustering dense TH-IR UWB are in proportion with the node density (or the number of nodes), while the upper bounds on the lifetime of extended networks are inversely proportional to the size of the deployment area (or the number of nodes). The results also reveal that the upper bound on the lifetime of dense network in the ideal case are longer than those of the static network by a factor of (n/log n)^1/2, and the upper bound on the lifetime of extended network in the ideal case are longer than those of the static network by a factor of (λn/log(λn))^1/2. Therefore, sensor nodes, or the Sink moving randomly in the square, can improve the lifetime of ordinary clustering TH-IR UWB sensor network.

Abstract:This paper proposes an implementation scheme of XACML (extensible access control markup language) policy evaluation engine based on multi-level optimization technology, MLOBEE (multi-level optimization based evaluation engine). Before evaluating these policies, the scenario implements rule refinement to lessen scale policies and adjust the sequence at the rule. During evaluation, the engine adopts a multi-cache mechanism that includes result cache, attribute cache, and policy cache to reduce the communication cost between engine and other components. To decrease matching magnitudes and enhance matching exactitudes, policy cache practices two stage index techniques. Finally, emulation tests validate that the overall evaluation performance of MLOBEE, using multi-level optimization technology, is better than most other similar systems.

Abstract:A remote attestation mechanism, with high efficiency, flexibility and privacy protection based on Merkle hash tree is proposed in this paper. The problems of IMA (integrity measurement architecture) architecture are analyzed for a special target application scenario; followed by a detailed description of RAMT (remote attestation mechanism based on Merkle hash tree) architecture and its process of integrity measuring and verifying. The function and pseudo-code of command TPM_HashTree, which is a function enhancement to the existing TPM (trusted platform module), are presented for the newly proposed mechanism. The advantages of the new mechanism are analyzed and discussed.