• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.525-543
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• 1998

This paper proposes a conceptual taxonomy of architectures far workflow management systems. The systematic classification work is based on a framework for workflow architectures. The framework, consisting of generic-level, conceptual-level and implementation-level architectures, provides common architectural principles for designing a workflow management system. We define the taxonomy by considering the possibilities for centralization or distribution of data, control, and execution. That is, we take into account three criteria. How are the major components of a workflow model and system, like activities, roles, actors, and workcases, concretized in workflow architecture？ Which of the components is represented as software modules of the workflow architecture？ And how are they configured and operating in the architecture？ The workflow components might be embodied, as active (processes or threads) modules or as passive (data) modules, in the software architecture of a workflow management system. One or combinations of the components might become software modules in the software architecture. Finally, they might be centralized or distributed. The distribution of the components should be broken into three: Vertically, Horizontally and Fully distributed. Through the combination of these aspects, we can conceptually generate about 64 software Architectures for a workflow management system. That is, it should be possible to comprehend and characterize all kinds of software architectures for workflow management systems including the current existing systems as well as future systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and "global perspective" to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed, compared, and contrasted. Added clarity is obtained because similar architectures from different vendors that used different terminology and techniques can now be seen to be identical at the higher level. Much of the complexity can be removed by thinking of workflow systems. Therefore, it is used to categorize existing workflow architectures and suggest a plethora of new workflow architectures. Finally, the taxonomy can be used for sorting out gems and stones amongst the architectures possibly generated. Thus, it might be a guideline not only for characterizing the existing workflow management systems, but also for solving the long-term and short-term architectural research issues, such as dynamic changes in workflow, transactional workflow, dynamically evolving workflow, large-scale workflow, etc., that have been proposed in the literature.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.26-51
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• 2003

Large scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in thePDB. PSIMAP incorporates both functional and evolutionary information into a single network. It makes it possible to age protein domains in terms of taxonomic diversity, interaction and function. One consequence of it is to predict the most important protein domain structure in evolution. We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: ${\bullet}$ Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. ${\bullet}$ Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. ${\bullet}$ Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. This led to the prediction of the oldest and most important protein domain in evolution of lift. ${\bullet}$ Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.421-433
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• 2012

AMGA service, which is one of the EMI gLite middleware components, is widely used for analysis of distributed large scale experiments data as metadata repository by scientific and technological researchers and the use of AMGA is extended farther to include general industries needing metadata Catalogue as well. However AMGA, based unix and Grid UI, has the weakness of being absence of general-purpose user interfaces in comparison to other commercial database systems and that's why it's difficult to use and diffuse it although it has the superiority of the functionality. In this paper, we developed AMGA GUI toolkit to provide work convenience using object-oriented modeling language(UML). Currently, AMGA has been used as the main component among many user communities such as Belle II, WISDOM, MDM, and so on, but we expect that this development can not only lower the barrier to entry for AMGA beginners to use it, but lead to expand the use of AMGA service over more communities.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.608-614
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• 2006

The popularization of high-speed networks and the innovation of high-performance hardware/servers have enlarged the role of large-scale, highly distributed IT infrastructure. Though many criteria on the assessment of IT infrastructure can be considered, the survivability assessment is treated as the most important one due to the essential role as an infrastructure. While assessing the survivability of some given IT infrastructures, we can not only choose the best one among them but also improve their survivability by modifying their structure and security policies. In this paper, we propose a DMKB-based assessment system on the survivability of IT infrastructures, where DMKB is a kind of database which provides the known vulnerabilities and defense mechanism for many system components.

• Journal of Biomedical Engineering Research
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• v.26 no.6
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• pp.399-406
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• 2005

In these days, HIS(Hospital Information System) raise the quality of medical services by effective management of medical records. As computing environment was developed, it is possible to search information quickly. But, standard medical data exchange is not completed between medical clinic and another organ so far. In case of patient transfer, past medical record was not efficiently transmitted. It be feasible treatment delay or medical accident. It is trouble that medical records is transferred by a person and communicate with each other. Extensible Markup Language (XML) is a simple, very flexible text format derived from SGML. Originally designed to meet the challenges of large-scale electronic publishing, XML is also playing an increasingly important role in the exchange of a wide variety of data on the Web and elsewhere. Form in system of company product, relative organs that handle bio-signal data is each other dissimilar and integration and to transmit to supplement bottleneck this research uses XML. In this study, it is discussed about sharing of medical data using XML web technology to standard medical record between hospital and relative organization The data structure model was designed to manage bio-signal data and patient record. We experimented about data transmission and all-in-one between different systems (one make use of MS-SQL database system and the other manage existent bio-signal data in itself form in file in this research). In order to search and refer medical record, the web-based system was implemented. The system that can be shared medical data was tested to estimate the merits of XML. Implemented XML schema confirms data transmission between different data system and integration result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.83-91
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• 2006

Internet shopping mall has become a huge distribution channel with dramatic growth in recent years. The number of consumers has exponentially increased as the scale of shopping mall has been large so that shopping malls with thousands or millions of consumers become a general case. However, it is essential to evaluate whether current assortment of consumers is proper or not in the strategic aspect in order to operate Internet shopping mall effectively and gain profits. That is, it is important to evaluate whether consumer strategy of corporation is proper or not from the corporation. Despite this business importance, consumer assortment has not been evaluated well and related study is not sufficient. This study supposes a framework for consumer assortment evaluation, which evaluates whether consumer assortment of Internet shopping mall is proper or not. In the framework for consumer assortment evaluation, analysis data based on order data and consumer data in database is made. Then, four factors, consumer maintenance rate, consumer profitability, consumer securing rate and consumer conversion are setup, and 22 measurement indexes are drawn. Finally, a consumer assortment evaluation score card is made by integrating them. This study has applied a supposed framework to a domestic typical community based shopping mall, and it is expected that the evaluation result will be used as informant strategic information to operate the shopping mall effectively.

• Journal of the Korean Society for Railway
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• v.11 no.4
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• pp.364-370
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• 2008

In this paper, we proposed new sensor network architecture with autonomous robots based on beacon mode and implemented real time monitoring system in real test-bed environment. The proposed scheme offers beacon based real-time scheduling for reliable association process with parent nodes and dynamically assigns network address by using NAA (Next Address Assignment) mechanism. For the large scale multi-sensor processing, our real-time monitoring system accomplished the intelligent database processing, which can generate not only the alert messages to the civilians but also process various sensing data such as fire, air, temperature and etc. Moreover, we also developed mobile robot which can support network mobility. Though the performance evaluation by using real test-bed system, we illustrate that our proposed system demonstrates promising performance for emergence monitoring systems.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1193-1207
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• 2003

Various web applications are developed as the Internet is popularized in many fields. However, in most cases of web application development, systematic analysis is omitted and developers jump into the implementation. Therefore developers have difficulties with applying the development methods for a large scale project. The approach of creating an analysis models of a web application from a business model is proposed for the rapid and efficient development. The analysis process, tasks and techniques are proposed for this approach. The use case diagram and web page list are created from business modes that is depicted using the notation of UML activity diagram. The page diagram and logical / physical database models are created using the use case diagram and the web page list. These analysis models are refined during the detailed design phase. The efficiency of proposed method has been shown using a practical case study which reflects the development project of the web application for supporting the association of auto repair shops.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.205-217
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• 2018

Deep learning using convolutional neural networks (CNNs) is being studied in various fields of image recognition and these studies show excellent performance. In this paper, we compare the performance of CNN architectures, KCR-AlexNet and KCR-GoogLeNet. The experimental data used in this paper is obtained from PHD08, a large-scale Korean character database. It has 2,187 samples of each Korean character with 2,350 Korean character classes for a total of 5,139,450 data samples. In the training results, KCR-AlexNet showed an accuracy of over 98% for the top-1 test and KCR-GoogLeNet showed an accuracy of over 99% for the top-1 test after the final training iteration. We made an additional Korean character dataset with fonts that were not in PHD08 to compare the classification success rate with commercial optical character recognition (OCR) programs and ensure the objectivity of the experiment. While the commercial OCR programs showed 66.95% to 83.16% classification success rates, KCR-AlexNet and KCR-GoogLeNet showed average classification success rates of 90.12% and 89.14%, respectively, which are higher than the commercial OCR programs' rates. Considering the time factor, KCR-AlexNet was faster than KCR-GoogLeNet when they were trained using PHD08; otherwise, KCR-GoogLeNet had a faster classification speed.