Selective Querying for Adapting Hierarchical Web Service Compositions

Author(s):  
John Harney ◽  
Prashant Doshi

Web Service compositions (WSC) often operate in volatile environments where the parameters of the component services change during execution. To remain optimal, the WSC could adapt to these changes by querying the participating providers for their revised parameters. Previously, the value of changed information (VOC) has been utilized in simple WSCs to selectively query only those services whose revised parameters are expected to bring about significant changes in the composition. In many cases, however, in order to promote scalability, a WSC is formulated as a more complex, nested structure – a higher-level WSC may be composed of WSs and lower-level WSCs – inducing a natural hierarchy over the composition. This chapter presents a novel approach that extends the capabilities of VOC-driven querying to address the problem of adapting hierarchical WSCs. It shows how to compose and adapt hierarchical WSCs by first deriving a model of volatility for lower-level WSCs and then by descending down the levels of nesting and computing the VOC for WSCs at each level. Experimental results demonstrate that this approach provides an effective and efficient solution for complex, hierarchical WSCs.

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.


2016 ◽  
Vol 09 (03) ◽  
pp. 1650043 ◽  
Author(s):  
Haolin Wu ◽  
Jie Yang ◽  
Haibiao Chen ◽  
Feng Pan

Preferentially etching either carbon or silica from silicon oxycarbide (SiOC) created a porous network as an inverse image of the removed phase. The porous structure was analyzed by gas adsorption, and the experimental results verified the nanodomain structure of SiOC. This work demonstrated a novel approach for analyzing materials containing nanocomposite structures.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chun-Hui Wu ◽  
Chia-Wei Chen ◽  
Long-Sheng Kuo ◽  
Ping-Hei Chen

A novel approach was proposed to measure the hydraulic capacitance of a microfluidic membrane pump. Membrane deflection equations were modified from various studies to propose six theoretical equations to estimate the hydraulic capacitance of a microfluidic membrane pump. Thus, measuring the center deflection of the membrane allows the corresponding pressure and hydraulic capacitance of the pump to be determined. This study also investigated how membrane thickness affected the Young’s modulus of a polydimethylsiloxane (PDMS) membrane. Based on the experimental results, a linear correlation was proposed to estimate the hydraulic capacitance. The measured hydraulic capacitance data and the proposed equations in the linear and nonlinear regions qualitatively exhibited good agreement.


2013 ◽  
Vol 11 (06) ◽  
pp. 1343003 ◽  
Author(s):  
JING-DOO WANG

In this paper, three genomic materials — DNA sequences, protein sequences, and regions (domains) are used to compare methods of virus classification. Virus classes (categories) are divided by various taxonomic level of virus into three datasets for 6 order, 42 family, and 33 genera. To increase the robustness and comparability of experimental results of virus classification, the classes are selected that contain at least 10 instances, and meanwhile each instance contains at least one region name. Experimental results show that the approach using region names achieved the best accuracies — reaching 99.9%, 97.3%, and 99.0% for 6 orders, 42 families, and 33 genera, respectively. This paper not only involves exhaustive experiments that compare virus classifications using different genomic materials, but also proposes a novel approach to biological classification based on molecular biology instead of traditional morphology.


2021 ◽  
pp. 1-56
Author(s):  
Brandon Prickett

Abstract Since Halle (1962), explicit algebraic variables (often called alpha notation) have been commonplace in phonological theory. However, Hayes and Wilson (2008) proposed a variable-free model of phonotactic learning, sparking a debate about whether such algebraic representations are necessary to capture human phonological acquisition. While past experimental work has found evidence that suggested a need for variables in models of phonology (Berent et al. 2012, Moreton 2012, Gallagher 2013), this paper presents a novel mechanism, Probabilistic Feature Attention (PFA), that allows a variable-free model of phonotactics to predict a number of these phenomena. Additionally, experimental results involving phonological generalization that cannot be explained by variables are captured by this novel approach. These results cast doubt on whether variables are necessary to capture human-like phonotactic learning and provide a useful alternative to such representations.


Commercial-off-the-shelf (COTS) Simulation Packages (CSPs) are widely used in industry primarily due to economic factors associated with developing proprietary software platforms. Regardless of their widespread use, CSPs have yet to operate across organizational boundaries. The limited reuse and interoperability of CSPs are affected by the same semantic issues that restrict the inter-organizational use of software components and web services. The current representations of Web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging Semantic Web. The authors present new research that partially alleviates the problem of limited semantic reuse and interoperability of simulation components in CSPs. Semantic models, in the form of ontologies, utilized by the authors’ Web service discovery and deployment architecture, provide one approach to support simulation model reuse. Semantic interoperation is achieved through a simulation component ontology that is used to identify required components at varying levels of granularity (i.e. including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The research presented here is based on the development of an ontology, connector software, and a Web service discovery architecture. The ontology is extracted from example simulation scenarios involving airport, restaurant and kitchen service suppliers. The ontology engineering framework and discovery architecture provide a novel approach to inter-organizational simulation, by adopting a less intrusive interface between participants Although specific to CSPs this work has wider implications for the simulation community. The reason being that the community as a whole stands to benefit through from an increased awareness of the state-of-the-art in Software Engineering (for example, ontology-supported component discovery and reuse, and service-oriented computing), and it is expected that this will eventually lead to the development of a unique Software Engineering-inspired methodology to build simulations in future.


Author(s):  
Judy C.R. Tseng ◽  
Wen-Ling Tsai ◽  
Gwo-Jen Hwang ◽  
Po-Han Wu

In developing traditional learning materials, quality is the key issue to be considered. However, for high technical e-training courses, not only the quality of the learning materials but also the efficiency of developing the courses needs to be taken into consideration. It is a challenging issue for experienced engineers to develop up-to-date e-training courses for inexperienced engineers before further new technologies are proposed. To cope with these problems, a concept relationship-oriented approach is proposed in this paper. A system for developing e-training courses has been implemented based on the novel approach. Experimental results showed that the novel approach can significantly shorten the time needed for developing e-training courses, such that engineers can receive up-to-date technologies in time.


Author(s):  
Béatrice Bouchou ◽  
Denio Duarte ◽  
Mírian Halfeld Ferrari ◽  
Martin A. Musicante

The XML Messaging Protocol, a part of the Web service protocol stack, is responsible for encoding messages in a common XML format (or type), so that they can be understood at either end of a network connection. The evolution of an XML type may be required in order to reflect new communication needs, materialized by slightly different XML messages. For instance, due to a service evolution, it might be interesting to extend a type in order to allow the reception of more information, when it is available, instead of always disregarding it. The authors’ proposal consists in a conservative XML schema evolution. The framework is as follows: administrators enter updates performed on a valid XML document in order to specify new documents expected to be valid, and the system computes new types accepting both such documents and previously valid ones. Changing the type is mainly changing regular expressions that define element content models. They present the algorithm that implements this approach, its properties and experimental results.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Haitao He ◽  
Chun Shan ◽  
Xiangmin Tian ◽  
Yalei Wei ◽  
Guoyan Huang

Identifying influential nodes is important for software in terms of understanding the design patterns and controlling the development and the maintenance process. However, there are no efficient methods to discover them so far. Based on the invoking dependency relationships between the nodes, this paper proposes a novel approach to define the node importance for mining the influential software nodes. First, according to the multiple execution information, we construct a weighted software network (WSN) to denote the software execution dependency structure. Second, considering the invoking times and outdegree about software nodes, we improve the method PageRank and put forward the targeted algorithm FunctionRank to evaluate the node importance (NI) in weighted software network. It has higher influence when the node has lager value of NI. Finally, comparing the NI of nodes, we can obtain the most influential nodes in the software network. In addition, the experimental results show that the proposed approach has good performance in identifying the influential nodes.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Ying Jin ◽  
Guangming Cui ◽  
Yiwen Zhang

Service-oriented architecture (SOA) is widely used, which has fueled the rapid growth of Web services and the deployment of tremendous Web services over the last decades. It becomes challenging but crucial to find the proper Web services because of the increasing amount of Web services. However, it proves unfeasible to inspect all the Web services to check their quality values since it will consume a lot of resources. Thus, developing effective and efficient approaches for predicting the quality values of Web services has become an important research issue. In this paper, we propose UIQPCA, a novel approach for hybrid User and Item-based Quality Prediction with Covering Algorithm. UIQPCA integrates information of both users and Web services on the basis of users’ ideas on the quality of coinvoked Web services. After the integration, users and Web services which are similar to the target user and the target Web service are selected. Then, considering the result of integration, UIQPCA makes predictions on how a target user will appraise a target Web service. Broad experiments on WS-Dream, a web service dataset which is widely used in real world, are conducted to evaluate the reliability of UIQPCA. According to the results of experiment, UIQPCA is far better than former approaches, including item-based, user-based, hybrid, and cluster-based approaches.


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