• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• Journal of the Korean Society for information Management
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• v.19 no.2
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• pp.49-67
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• 2002

Nowadays an information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and database. Accordingly, A unified modeling methodology need to store the XML file on the variety database. In this paper, we propose a unified design methodology for XML applications based on variety databases using UML. To this goal, first we introduce a XML modeling methodology to design W3C XML schema using UML and second we propose data modeling methodology for object-relational database schema, object oriented database an schema and relational database schema to store efficiently XML data in databases.

• Proceedings of the CALSEC Conference
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• 1997.11a
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• pp.263-268
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• 1997

Functional Modeling methodology, IDEF0 is widely used for modeling, analysis and description of enterprise system. The limitation of modeling components restricts applicability and give rise to confusion about model. In this paper, we propose new method to extend IDEF0. The first is adding modeling components which are semantic representations. In addition to ICOMs, we add the time and cost component which is required to execute the function. The second is tracing mechanism. When we need some information, we drive the functions related with the information by reverse tracing of the function which produces the information as a output and input. Through the tracing, we find out the bottleneck process or high cost process. Finally, we suggest the final decomposition level. We call the final decomposed function into unit function which has only one output data. We can combine and reconstruct some of functions because an unit function is similar to ‘lego block’. To reach the integrated system, the main problem to be solved is the integration of information produced by different functional subsystem. This can be resolved when the creation of data must be dependent on only one function. Through view integration of function output, we can guarantee the integrity of data.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.408-417
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• 2005

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.

• Ocean Science Journal
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• v.42 no.1
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• pp.1-8
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• 2007

Acoustic volume backscattering strength data were collected and Conductivity Temperature Depth (CTD) measurements were conducted in the southern Yellow Sea in summer 2005 and 2006. The high temporal and vertical resolution acoustic data measured with a 307 kHz Acoustic Doppler Current Profiler (ADCP) and a 250 kHz acoustic Doppler profile (ADP) had dominant diel variation, which resulted from vertical migration of sound scatterers. Some scatterers congregating in the bottom layer in the daytime migrated upward at dusk, and migrated downward into the bottom layer at dawn. The migration speeds were estimated. More than 33 days data show that the diel migration varies with time. The feature of migration measured with ADCP and ADP is consistent to some extent with what is described in the study on vertical migration of zooplankton in the southern Yellow Sea with conventional net samples.

• Journal of Environmental Impact Assessment
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• v.19 no.3
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• pp.315-321
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• 2010

ArcView and water network models have been integrated to develop the water network modeling system based upon GIS. To develop this system, pre, main, and post processing systems are required. GIS programming technique was adopted by using the ArcView's script language Avenue. The input data of models have been prepared by using the AutoCAD Map3D through the conversion of modeling input data to GIS data for A city. The modeling has been implemented by using EPANET, WaterCAD, InfoWorks. To develop the post processing system, the modeling results of the water network models have been analyzed by using GIS. During the application process of the developed system to B city with 300,000 population, main problems were found in the constructed GIS DB of that city. Thus, pilot study area of B city has been constructed, and pre-, main, and post-processing techniques were invented based upon GIS. Finally, the problems related to waterworks GIS projects in Korea were discussed and solutions were suggested.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.2
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• pp.153-162
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• 2011

The demands of complicated data communications have issued a new challenge to port logistics systems. Customers expect ports to handle their generated administrative data while a vessel is docked in a port. One port logistics system, known as the Vessel Clearance Process (VCP), manages large numbers of documents related to port of entry. In the VCP, information flows through many organizations such as the port authority, shipping agents, marine offices, immigration offices, and others. Therefore, for effective management of the Business Process (BP) of the VCP, a standardized method of BP modeling is essential, especially in heterogeneous system environments. In a port, according to port policy, terms and data are sued that are similar to but different from those of other logistics partners, which hinders standardized modeling of the BP. In order to avoid tedious and time-consuming document customization work, more convenient modeling of BP for VCP is essential. This paper proposes an ontology-based process similarity measurement to assist designer for process modeling in port domain, especially VCP. We expect that this methodology will use convenient and quick modeling of port business processes.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.34-43
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• 2006

This paper shows modeling methods for VBR video trace. It is well known that VBR video trace is characterized as longterm correlated and highly intermittent burst data. To analyze this, we attempt to model it using neural network with auxiliary linear structures derived from residual threshold. For testing purpose, we generate VBR video trace from chaotic nonlinear function combined with the geometric random noise. The modeling result of the generated data shows that the attempted method represents more accurately than the traditional neural network. However, we also found that combining hRU to the attempted modeling method can yield a closer agreement to statistical features of the generated data than the attempted modeling method alone.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.182-187
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• 2007

A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.13-18
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• 2019

In this study, we investigate important keywords and their relationships among the keywords for social issues, and analyze topics to find subjects of the social issues. In particular, we collected twitter data with the keyword 'metoo' which has attracted much attention in these days, and perform keyword analysis and topic modeling. First, we preprocess the twitter data, identified important keywords, and analyzed the relatedness of the keywords. After then, topic modeling is performed to find subjects related to 'metoo'. Our experimental results showed that relatedness of keywords and subjects on social issues in twitter are well identified based on keyword analysis and topic modeling.