UniFlexView : a unified framework for consistent construction of BPMN and BPEL process views
- Authors: Yongchareon, Sira , Liu, Chengfei , Zhao, Xiaohui
- Date: 2020
- Type: Text , Journal article
- Relation: Concurrency Computation Vol. 32, no. 11 (2020), p.
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- Description: Process view technologies allow organizations to create different granularity levels of abstraction of their business processes, therefore enabling a more effective business process management, analysis, interoperation, and privacy controls. Existing research proposed view construction and abstraction techniques for block-based (ie, BPEL) and graph-based (ie, BPMN) process models. However, the existing techniques treat each type of the two types of models separately. Especially, this brings in challenges for achieving a consistent process view for a BPEL model that derives from a BPMN model. In this paper, we propose a unified framework, namely UniFlexView, for supporting automatic and consistent process view construction. With our framework, process modelers can use our proposed View Definition Language to specify their view construction requirements disregarding the types of process models. Our UniFlexView's system prototype has been developed as a proof of concept and demonstration of the usability and feasibility of our framework. © 2019 John Wiley & Sons, Ltd.
A detector of structural similarity for multi-modal microscopic image registration
- Authors: Lv, Guohua , Teng, Shyh , Lu, Guojun
- Date: 2018
- Type: Text , Journal article
- Relation: Multimedia Tools and Applications Vol. 77, no. 6 (2018), p. 7675-7701
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- Description: This paper presents a Detector of Structural Similarity (DSS) to minimize the visual differences between brightfield and confocal microscopic images. The context of this work is that it is very challenging to effectively register such images due to a low structural similarity in image contents. To address this issue, DSS aims to maximize the structural similarity by utilizing the intensity relationships among red-green-blue (RGB) channels in images. Technically, DSS can be combined with any multi-modal image registration technique in registering brightfield and confocal microscopic images. Our experimental results show that DSS significantly increases the visual similarity in such images, thereby improving the registration performance of an existing state-of-the-art multi-modal image registration technique by up to approximately 27%. © 2017, Springer Science+Business Media New York.
COREG : A corner based registration technique for multimodal images
- Authors: Lv, Guohua , Teng, Shyh , Lu, Guojun
- Date: 2018
- Type: Text , Journal article
- Relation: Multimedia Tools and Applications Vol. 77, no. 10 (2018), p. 12607-12634
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- Description: This paper presents a COrner based REGistration technique for multimodal images (referred to as COREG). The proposed technique focuses on addressing large content and scale differences in multimodal images. Unlike traditional multimodal image registration techniques that rely on intensities or gradients for feature representation, we propose to use contour-based corners. First, curvature similarity between corners are for the first time explored for the purpose of multimodal image registration. Second, a novel local descriptor called Distribution of Edge Pixels Along Contour (DEPAC) is proposed to represent the edges in the neighborhood of corners. Third, a simple yet effective way of estimating scale difference is proposed by making use of geometric relationships between corner triplets from the reference and target images. Using a set of benchmark multimodal images and multimodal microscopic images, we will demonstrate that our proposed technique outperforms a state-of-the-art multimodal image registration technique. © 2017, Springer Science+Business Media, LLC.
Automatic image search based on improved feature descriptors and decision tree
- Authors: Hou, Jin , Chen, Zeng , Qin, Xue , Zhang, Dengsheng
- Date: 2011
- Type: Text , Journal article
- Relation: Integrated Computer-Aided Engineering Vol. 18, no. 2 (2011), p. 167-180
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- Description: There has been a growing interest in implementing image search engine at the semantic level. However, most existing practical systems including popular commercial image search engines like Google and Yahoo! are either text-based or a simple hybrid of texts and visual features. This paper proposes a novel image search system based on automatic image annotation. We develop a technology which learns semantic image concepts from image contents and transforms unstructured images into textual documents, so that images are indexed and retrieved in the same way as textual documents. Existing database management systems can be used to effectively manage image contents, and image search can be as efficient as text search by transforming images into textual documents through machine learning. Experiments in both the Corel dataset and real Web dataset are performed to validate our system and the results are promising. This system suggests a new combination of texts and visual features in order to achieve a semantic image search, and is expected to become a re-ranking system to the existing image search result via the Internet.
How to improve postgenomic knowledge discovery using imputation
- Authors: Sehgal, Muhammad Shoaib B , Gondal, Iqbal , Dooley, Laurence , Coppel, Ross
- Date: 2009
- Type: Text , Journal article
- Relation: Eurasip Journal on Bioinformatics and Systems Biology Vol. 2009, no. 1 (2009), p. 1-14
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- Description: While microarrays make it feasible to rapidly investigate many complex biological problems, their multistep fabrication has the proclivity for error at every stage. The standard tactic has been to either ignore or regard erroneous gene readings as missing values, though this assumption can exert a major influence upon postgenomic knowledge discovery methods like gene selection and gene regulatory network (GRN) reconstruction. This has been the catalyst for a raft of new flexible imputation algorithms including local least square impute and the recent heuristic collateral missing value imputation, which exploit the biological transactional behaviour of functionally correlated genes to afford accurate missing value estimation. This paper examines the influence of missing value imputation techniques upon postgenomic knowledge inference methods with results for various algorithms consistently corroborating that instead of ignoring missing values, recycling microarray data by flexible and robust imputation can provide substantial performance benefits for subsequent downstream procedures