• Molecules and Cells
• /
• v.28 no.5
• /
• pp.463-472
• /
• 2009

Although the possible cellular roles of several ubiquitin-specific proteases (UBPs) were identified in Arabidopsis, almost nothing is known about UBP homologs in rice, a monocot model plant. In this report, we searched the rice genome database (http://signal.salk.edu/cgi-bin/RiceGE) and identified 21 putative UBP family members (OsUBPs) in the rice genome. These OsUBP genes each contain a ubiquitin carboxyl-terminal hydrolase (UCH) domain with highly conserved Cys and His boxes and were subdivided into 9 groups based on their sequence identities and domain structures. RT-PCR analysis indicated that rice OsUBP genes are expressed at varying degrees in different rice tissues. We isolated a full-length cDNA clone for OsUBP6, which possesses not only a UCH domain, but also an N-terminal ubiquitin motif. Bacterially expressed OsUBP6 was capable of dismantling K48-linked tetra-ubiquitin chains in vitro. Quantitative real-time RT-PCR indicated that OsUBP6 is constitutively expressed in different tissues of rice plants. An in vivo targeting experiment showed that OsUBP6 is predominantly localized to the nucleus in onion epidermal cells. We also examined how knock-out of OsUBP6 affects developmental growth of rice plants. Although homozygous T3 osubp6 T-DNA insertion mutant seedlings displayed slower growth relative to wild type seedlings, mature mutant plants appeared to be normal. These results raise the possibility that loss of OsUBP6 is functionally compensated for by an as-yet unknown OsUBP homolog during later stages of development in rice plants.

• International Journal of Aeronautical and Space Sciences
• /
• v.6 no.1
• /
• pp.52-60
• /
• 2005

The CFD coupled aeroelastic analyses have significant advantages over linear panel methods in their accuracy and usefulness for the simulation of actual aeroelastic motion after specific initial disturbance. However, in spite of their advantages, a heavy computation time is required. In this paper, a method is discussed to save a computational cost in the time domain aeroelastic analysis based on the system identification technique. The coefficients of system identification model are fit to the computed time response obtained from a previously developed aeroelastic analysis code. Because the non-dimensionalized data is only used to construct the model structure, the resulting model of the unsteady CFD solution is independent of dynamic pressure and this independency makes it possible to find the flutter dynamic pressure without the unsteady aerodynamic computation. To confirm the accuracy of the system identification methodology, the system model responses are compared with those of the CFD coupled aeroelastic analysis at the same dynamic pressure.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.219-227
• /
• 2020

Smart Factory is one of the fastest developing and changing fourth industrial revolution fields. In particular, the degree of introduction and maturity level in the smart factory is an important part. In this paper, a cluster analysis of companies introduced smart factory was performed based on a new maturity assessment model. The 68% of 193 companies surveyed were at the basic level, with only 21% being the middle one. Most SMEs cited lack of funds as the main reason for not entering the middle one. As a result of the cluster analysis, it was found that all clusters had similar patterns but grouped into one of three levels of high, middle, and low depending on maturity level of smart factory operation, and process domain had the highest maturity and data domain was lowest among the 6 domains. Through this, analysis of more specific and quantified maturity levels can be performed using 6-domain smart factory maturity evaluation model.

• Journal of Korean Library and Information Science Society
• /
• v.47 no.4
• /
• pp.289-307
• /
• 2016

This paper introduces a software system and process model for constructing domain-specific relation extraction datasets semi-automatically. The system uses a set of terms such as genes, proteins diseases and so forth as inputs and then by exploiting massive biological interaction database, generates a set of term pairs which are utilized as queries for retrieving sentences containing the pairs from scientific databases. To assess the usefulness of the proposed system, this paper applies it into constructing a genic interaction dataset related to Alzheimer's disease domain, which extracts 3,510 interaction-related sentences by using 140 gene names in the area. In conclusion, the resulting outputs of the case study performed in this paper indicate the fact that the system and process could highly boost the efficiency of the dataset construction in various subfields of biomedical research.

• The Journal of Information Systems
• /
• v.5
• /
• pp.149-173
• /
• 1996

This paper focus on the development of object-oriented model bases for Structured Modeling. For the model base organization, object modeling techniques and model typing concept which is similar to data typing concept are used. Structured modeling formalizes the notion of a definitional system as a way of dscribing models. From the object-oriented concept, a structured model can be represented as follows. Each group of similar elements(genus) is represented by a composite class. Other type of genera can be represented in a similar manner. This hierarchical class composition gives rise to an acyclic class-composition graph which corresponds with the genus graph of structured model. Nodes in this graph are instantiated to represent the elemental graph for a specific model. Taking this class composition process one step further, we aggregate the classes into higher-level composite classes which would correspond to the structured modeling notion of a module. Finally, the model itself is then represented by a composite class having attributes each of whose domain is a composite class representing one of the modules. The resulting class-composition graph represent the modular tree of the structured.

• Journal of Fisheries and Marine Sciences Education
• /
• v.20 no.3
• /
• pp.462-472
• /
• 2008

Education is a field that has tried to make use of the advantages of computers since they were introduced to the world. Intelligent Tutoring System and multimedia have become methods of teaching students of Computer Science, Education, Psychology, and Cognitive Science. Until now, they have been designed and produced only on the basis of a very specific domain and format. However, in the education field, most learners ask for integrated service that is practical, realizable, and sensitive to technological change. Therefore, in this study, we would like to present the technological and formal integration model as an ITS model which acknowledges changes in the fields of technology and education. As a technological integration model, the integration model of traditional Symbolic Artificial Intelligence and Artificial Neural Networks was presented. As a formal integration model, three integration models were presented according to (a) the process of learning diagnosis (b) learners' action behaviors (c) intelligence service respectively.

• Journal of the Korean Statistical Society
• /
• v.31 no.3
• /
• pp.277-299
• /
• 2002

Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.63-70
• /
• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.249-255
• /
• 2005

Angiotensin-converting enzyme (ACE) is primarily responsible for human hypertension. Current ACE drugs show serious cough and angiodema health problems due to the un-specific activity of the drug to ACE protein. The availability of ACE crystal structure (1UZF) provided the plausible biological orientation of inhibitors to ACE active site (C-domain). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecula. field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of 28 ACE inhibitors. Alignment for CoMFA obtained by docking ligands to 1UZF protein using FlexX program showed better statistical model as compared to superposition of corresponding atoms. The statistical parameters indicate reasonable models for both CoMFA (q$^2$ = 0.530, r$^2$ = 0.998) and CoMSIA (q$^2$= 0.518, r$^2$ = 0.990). The 3D-QSAR analyses provide valuable information for the design of ACE inhibitors with potent activity towards C-domain of ACE. The group substitutions involving the phenyl ring and carbon chain at the propionyl and sulfonyl moieties of captopril are essential for specific activity to ACE.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.511-515
• /
• 2001

Many intelligent agent systems are known to incorporate BDI architecture for cognitive reasoning. Since this architecture contains all the knowledge of world model and reasoning rule, it is very complex and difficult to handle. This paper describes a methodology to design and implement BDI architecture, BDIAXml based on XML for multi-agent systems. This XML-based BDI architecture is smaller than any other BDI architecture because it separates knowledge for reasoning from domain knowledge and enables knowledge sharing using XML technology. Knowledge for BDI mental state and reasoning is composed of specific XML files and these XML files are stored into a specific knowledge server. Most systems using BDIAxml architecture can access knowledge from this server. We apply this BDIAXml system to domain of Hospital Information System and show that this architecture performs more efficiently than other BDI architecture system in terms of knowledge sharing, system size, and ease of use.