7197821
A case study on system-level modeling by aspect-oriented programming
The paper presents a novel and synergistic system-level modeling approach based on aspect-oriented programming (AOP) and SystemC. A case study on a 128-bit binary floating-point adder is performed to demonstrate the modeling strength of the approach. The validation experiment shows the effectiveness of the proposed approach. This work constitutes a first attempt to employ AOP in modeling digital systems.
15772260
DHT-Based Range Query Processing for Web Service Discovery
DHTs are scalable, self-organizing, and adaptive to underlying topology changes, thus being a promising infrastructure for realizing efficient Web service discovery. Range queries play an important role in service discovery, and in recent years a number of DHT-based range query schemes have been proposed. However, most of them suffer from high query delay and high processing cost. This paper presents ERQ, an Efficient scheme for delay bounded Range Query processing over DHTs. We first emulate the PHT structure and design a balanced Kautz (BK) tree to uniformly map the m-dimensional data space onto DHT nodes, and then present a novel algorithm that processes range queries in a parallel fashion, where an on-the-fly space pruning mechanism is adopted to reduce the processing cost. In a DHT with N nodes, ERQ can answer any range query in less than logN (2loglogN+1) hops with low processing cost, irrespective of the queried range, the whole space size, or the number of queried attributes. The effectiveness of ERQ is demonstrated through extensive experiments.
31126370
Transform BPEL Workflow into Hierarchical CP-Nets to Make Tool Support for Verification
Availability of a wide variety of Web services over the Internet offers opportunities of providing new value added services by composing existing ones. Service composition poses a number of challenges. A composite service can be very complex in structure, containing many temporal and data-flow dependencies between the component services. It is highly desirable therefore to be able to validate that a given composite service is well formed: proving that it will not deadlock or livelock and that it respects the sequencing constraints of the constituent services. In this paper, we propose an approach of composition analysis and verification based on Colored Petri nets (CP-nets), which is an extended version of Petri Nets, which have a sound mathematical semantics and a number of existing analysis tools. We provide translation rules of web composition language into CP-nets and a technique to analyze and verify effectively the net to investigate several behavioral properties. Our translation technique is essentially independent of which language we describe composition. As an example, to show the effectiveness of our technique, we pick up BPEL and translate the BPEL specification into CP-nets in a constructive way. These nets are analyzed and verified as prototypes of the specification.
15977207
Exploiting hierarchical CP-nets to increase the reliability of Web services workflow
Individual Web services can be composed together to form value-added composite Web services represented as business process workflow. However, the value of such composite Web services is directly influenced by the reliability of the composite services. Composing Web services is not an easy task and is error-prone, so there is a growing interest for the verification techniques which enable designers to find and repair design errors even before actual running of the service, or allow designers to detect erroneous properties such as deadlocks or livelocks and formally verify whether the service process design does have certain desired properties (such as consistency with the conversation protocols of partner service). In this paper, we present to analyze and verify Web services composition by using some kind of colored Petri nets (CP-nets) called hierarchical CP-nets, which combine the strengths of Petri nets with the expressive power of high-level programming and have sound mathematical semantics. Services composition proposals can be transformed by transformation rules into CP-nets, which can be simulated to analyze the performance and verified to investigate behavioral properties by exploiting existing CP-nets specialized tools
33185687
Supremum of Agent Number Needed in Analyzing Security Protocols Based on Horn Logic
17985803
Verifying Web Services Composition: A Transformation-Based Approach
Web services composition is an emerging paradigm for enabling application integration. BPEL is a promising language describing composition in form of business processes, but is lack of sound formal semantic. This paper presents the transformation of BPEL to CP-nets in a constructive way. Therefore we can translate composition specified in BPEL into CPnets, which can be analyzed and verified by many specialized tools. So we make tool support available for verifying BPEL composition.
28340796
Tests on Symmetry and Continuity between BSIM4 and BSIM5
This paper presents the test results on the CMOS model symmetry and continuity characteristics between BSIM4 and BSIM5 from University of California at Berkeley. It is shown that the industry standard model BSIM4 has a series of the shortcomings of the continuity and symmetry, such as the charge, high-order current derivatives, and the trans-capacitances while new generation BSIM MOSFET compact model, BSIM5, demonstrates all necessary continuity and symmetry characteristics, which are very important for analog and RF circuit design
45720537
Bayesian Network Structure Ensemble Learning
Bayesian networks (BNs) have been widely used for learning model structures of a domain in the area of data mining and knowledge discovery. This paper incorporates ensemble learning into BN structure learning algorithms and presents a novel ensemble BN structure learning approach. Based on the Markov condition and the faithfulness condition of BN structure learning, our ensemble approach proposes a novel sample decomposition technique and a components integration technique. The experimental results reveal that our ensemble BN structure learning approach can achieve an improved result compared with individual BN structure learning approach in terms of accuracy.
1280778
Splice Site Prediction using Support Vector Machines with Context-Sensitive Kernel Functions
This paper focuses on the use of support vector machines on a typical context-dependent classification task, splice site prediction. For this type of problems, it has been shown that a context-based approach should be preferred over a transfor- mation approach because the former approach can easily incorporate statistical mea- sures or directly plug sensitivity information into distance functions. In this paper, we designed three types of context-sensitive kernel functions: polynomial-based, radial basis function-based and negative distance-based kernels. From the experimental re- sults it becomes clear that the radial basis function-based kernel with information gain weighting gets the best accuracies and can always outperform their simple non-sensitive counterparts both in accuracy and in model complexity. And with well designed fea- tures and carefully chosen context sizes, our system can predict splice sites with fairly high accuracy, which can achieve the FP95% rate, 3.94 for donor sites and 5.98 for acceptor sites, an approximate state of the art performance for the moment.
159232383
Paradoxes review
I came across one of the Smarandache divine paradoxes and felt very strongly that it is really our Buddhist's obligation to help understand the underlying truth. There seem a lot of toughest points in the cultural difference, and it will be the most difficult job to reach the mutual point as neutrality. What I can do is to try our best and find cooperation. Limited to the time, I just put a few as my first review.
35354920
Color text image binarization based on binary texture analysis
In this paper, a novel binarization algorithm for color text images is presented. This algorithm effectively integrates color clustering and binary texture analysis, and is capable of handling situations with complex backgrounds. In this algorithm, dimensionality reduction and graph theoretical clustering are first employed. As the result, binary images related to clusters can be obtained. Binary texture analysis is then performed on each candidate binary image. Two kinds of effective texture features, run-length histogram and spatial-size distribution related respectively, are extracted and explored. Cooperating with an LDA classifier, the optimal candidate of the best binarization effect is obtained. Experiments with images collected from Internet has been carried out and compared with existing techniques, both show the effectiveness of the algorithm.