• Journal of the Korea Society for Simulation
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• v.16 no.4
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• pp.77-86
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• 2007

Web services are considered as the critical component in the business plans of corporations as they offers the potential for creating highly dynamic and versatile distributed applications that span across business boundaries. Web Service Orchestration studies composition of already-existing web services to create new value-added services. The composite web services could be executed in a centralized or peer-to-peer(P2P) orchestration model. Compared with centralized-orchestration model, the P2P-based orchestration model provides better scalability, reliability, and performance for the overall services. However, recent P2P-orchestration solutions have limitation in supporting complex workflow patterns. Therefore, they could not effectively handle sophisticated business workflow, which contains complex workflow patterns. In this paper, we propose the WORKGLOW system, which can deal with complex workflow patterns while it is able to perform composite services in P2P orchestration manner. Comparing with centralized orchestration systems, the WORKGLOW brings up more business logic advantages, better performance, and higher flexibility with only a little overhead.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.603-615
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• 2005

As recent business environments are changed and become complex, a more efficient and effective business process management are needed. This paper proposes a new approach to the automatic execution of business processes using Event-Condition-Action (ECA) rules that can be automatically triggered by an active database. First of all, we propose the concept of blocks that can classify process flows into several patterns. A block is a minimal unit that can specify the behaviors represented in a process model. An algorithm is developed to detect blocks from a process definition network and transform it into a hierarchical tree model. The behaviors in each block type are modeled using ACTA formalism. This provides a theoretical basis from which ECA rules are identified. The proposed ECA rule-based approach shows that it is possible to execute the workflow using the active capability of database without users' intervention.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.