• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.147-160
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• 2008

BPMS(business process management system) facilitates defining new processes or updating existing processes. However, processing of exceptional or nonroutine task requires the intervention of domain experts or introduction of the situation specific resolution process. This paper assumes sufficient amount of business process exception handling cases are stored in the process repository. Since the retrieval of the best exception handling process requires a good understanding about the exceptional situation, context awareness is an important issue. To facilitate the understanding of exceptional situation and to enable the efficient selection of the best exception handling process, we adopted the 'situation variable' and 'decision variable' construct. A case example for exception handling in the e-commerce delivery process is provided to illustrate how the proposed construct works. Application of the C5.0 algorithm guarantees the construction of an optimum search tree. It also implies that an efficient search path has been identified for the context aware selection of the best exception handling process.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.109-116
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• 2012

The effect of the grid resolution on the hydrodynamic simulation has been investigated by using CCHE2D and EFDC. Since a high resolution of the grid results in the increase of computation time, an appropriate grid resolution should be selected by considering the efficiency of simulation according to the objectives of projects. In order to understand the effect of grid resolution and determine the optimal grid resolution, several cases with different lateral grid resolutions have been simulated for the reach of Nakdong river at the confluence of Kumho river for the floods in 2006. Orthogonal curvilinear grids for the domain have been constructed from the survey products at the sections with the longitudinal interval of 20 m. Area-elevation curve and the comparison of simulated results with measured stage at the specific station have been used to check the effect of grid resolution. From the results, the existence of optimal grid resolution has been observed, which ensure both efficiency of computation and certainty of results.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.1-13
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• 2004

The effect of Application system with class units is not sufficient because of independency and reuse of Component elements due to component abstraction based on only source code. Therefore We need to apply design pattern approach to represent not only the problem abstraction but also information and relationship between system elements for generic solutions of specific domain, Also, it is essential to software reverse engineering acquiring the correct understandings of the system through examining the existing systems and utilizing the acquired knowledges as reusable resources. In this paper, the extraction algorithm with JAVA and the validity of applying reverse engineering with extracting design patterns from source codes of the existing object-oriented system; are devised. The architecture of automatic tool is designed and implemented for 1) automatic extraction of design patterns and 2) reuse tool for retrieving, editing and rebuilding of design patterns.

• Spatial Information Research
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• v.19 no.6
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• pp.87-100
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• 2011

Recently, a variety of GML application schemas have been designed in many fields. GML application schemas are specific to the application domain of interest and specify object types using primitive object types defined in the GML standard. GML instance documents are created based on such GML application schemas. The GML instance documents generally require large volumes to represent huge amounts of geographic objects. Thus, it is essential to store such GML instance documents in relational database for efficient management and use. Relational database is relatively convenient to use and is widely applied in various fields. Furthermore, it is fundamentally more efficient than file structure to handle large datasets. Many researches on storing GML documents have been carried out so far. However, there are few studies on storage of GML instance documents. Therefore, in this study, we developed the storage module to store the GML instance documents in relational database.

• The Journal of Information Systems
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• v.21 no.1
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• pp.1-17
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• 2012

Common Method Bias(CMB) may cause the potential inflation of correlations between measures assessed via the same method. The problem of CMB has been well known in behavioral sciences because the survey method with self-reporting is vulnerable to CMB. Thus, the discussion on CMB is still ongoing in the MIS research in US. However, in Korea, the MIS research has never paid attention on the CMB problem. The purpose of this study is to examine the CMB problem in the Korean MIS research. To evaluate the effect of CMB, empirical studies on Technology Acceptance Model(TAM) are selected because (1) TAM is one of the MIS research areas studied intensively, (2) TAM is a theoretical model well supported by the existing empirical studies so that the result of this study would have a great ripple effect when the CMB problem turned out to be serious, (3) CMB is domain-specific. 47 TAM samples (out of 45 studies) from three Korean Journals were selected and the relevant data were collected such as correlation matrixes and the measures of the dependent variable. To find and evaluate the size of CMB, two analytic methods (Marker-Variable Technique and Method-Method Pair Technique) are employed. The result showed that there exists CMB in the Korean studies but the problem is not so serious to distort the empirical testing, compared with that of US studies. However, considering that CMB can contaminate the testing results, Korean MIS researchers should explicitly deal with the problem in designing empirical studies and collecting data.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.157-165
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• 2021

Recently, studies using deep learning to analyze a large amount of text are being actively conducted. In particular, a pre-trained language model that applies the learning results of a large amount of text to the analysis of a specific domain text is attracting attention. Among various pre-trained language models, BERT(Bidirectional Encoder Representations from Transformers)-based model is the most widely used. Recently, research to improve the performance of analysis is being conducted through further pre-training using BERT's MLM(Masked Language Model). However, the traditional MLM has difficulties in clearly understands the meaning of sentences containing new words such as newly coined words. Therefore, in this study, we newly propose NTM(Newly coined words Target Masking), which performs masking only on new words. As a result of analyzing about 700,000 movie reviews of portal 'N' by applying the proposed methodology, it was confirmed that the proposed NTM showed superior performance in terms of accuracy of sensitivity analysis compared to the existing random masking.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.275-287
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• 2024

Research on the integration of Knowledge Graphs (KGs) and Language Models (LMs) has been consistently explored over the years. However, studies focusing on the automatic generation of text using the structured knowledge from KGs have not been as widely developed. In this study, we propose a methodology for automatically generating specific domain-related research items (Related Work) at a level comparable to existing papers. This methodology involves: 1) selecting optimal prompts, 2) extracting triples through a four-step refinement process, 3) constructing a knowledge graph, and 4) automatically generating related research. The proposed approach utilizes GPT-4, one of the large language models (LLMs), and is desigend to automatically generate related research by applying the four-step refinement process. The model demonstrated performance metrics of 17.3, 14.1, and 4.2 in Triple extraction across #Supp, #Cont, and Fluency, respectively. According to the GPT-4 automatic evaluation criteria, the model's performamce improved from 88.5 points vefore refinement to 96.5 points agter refinement out of 100, indicating a significant capability to automatically generate related research at a level similar to that of existing papers.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.91-107
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• 2012

As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1332-1339
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• 2001

SoC(System on Chip) technology is widely used in the field of embedded systems by providing high flexibility for a specific application domain. An important aspect of development any new embedded system is verification which usually requires lengthy software and hardware co-design. To reduce development cost of design effort, the instruction set of microprocessor must be suitable for a high level language compiler. And FPGA prototype system could be derived and tested for design verification. In this paper, we propose a 16 bit FPGA microprocessor, which is tentatively-named EISC16, based on an EISC(Extendable Instruction Set Computer) architecture for embedded applications. The proposed EISC16 has a 16 bit fixed length instruction set which has the short length offset and small immediate operand. A 16 bit offset and immediate operand could be extended using by an extension register and an extension flag. We developed a cross C/C++ compiler and development software of the EISC16 by porting GNU on an IBM-PC and SUN workstation and compared the object code size created after compiling a C/C. standard library, concluding that EISC16 exhibits a higher code density than existing 16 microprocessors. The proposed EISC16 requires approximately 6,000 gates when designed and synthesized with RTL level VHDL at Xilinix's Virtex XCV300 FPGA. And we design a test board which consists of EISC16 ROM, RAM, LED/LCD panel, periodic timer, input key pad and RS-232C controller. 11 works normally at 7MHz Clock.