• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.827-836
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• 2001

The PID controller has been widely applied to the most control systems because of its simple structure and east designing. One of the important points to design the PID control system is to tune the approximate control parameters for the given target system. To find the PID parameters using Ziegler Nichols(ZN) method needs a lot of experience and experiments to ensure the optimal performance. In this paper, CMIA(Cell Mediated Immune Algorithm) controller is proposed to drive the autonomous guided vehicle (AGV) more effectively. The proposed controller is based on specific immune responses of the biological immune system which is the cell mediated immunity. To verify the performance of the proposed CMIA controller, some experiments for the control of steering and speed of that AGV are performed. The tracking error of the AGV is mainly investigated for this purpose. As a result, the capability of realization and reliableness are proved by comparing the response characteristics of the proposed CMIA controllers with those of the conventional PID and NNPID(Neural Network PID) controller.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.1
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• pp.12-16
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• 2004

Partitioning of human granulocyte-macrophage colony stimulating factor (hGM-CSF) was achieved in the aqueous two-phase systems (ATPSs) using a crude extract of transgenic tobacco cell suspension culture. This study examined the effects of polyethylene glycol (PEG) molecular weight and concentration and the effects of sodium phosphate concentration in different PEG/sodium phosphate systems on the partition coefficient, K. The best ATPS system was 5% PEG 8,000/1.6 M sodium phosphate after 2 h of incubation at room temperature. In this system, hGM-CSF was partitioned in the PEG-rich phase with a yield of 57.99% and K$\_$hGM-CSF/ of 8.12. In another system, 3% PEG 10,000/1.6 M sodium phosphate, hGM-CSF was also partitioned primarily in the top phase with a yield of 45.66% and K$\_$hGM-CSF/ of 7.64 after 2 h of incubation at room temperature.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.388-391
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• 2005

The Protein Structural and Functional Conservation need a common language for data definition. With the help of common language provided by Protein Ontology the high level of sequence and functional conservation can be extended to all organisms with the likelihood that proteins that carry out core biological processes will again be probable orthologues. The structural and functional conservation in these proteins presents both opportunities and challenges. The main opportunity lies in the possibility of automated transfer of protein data annotations from experimentally traceable model organisms to a less traceable organism based on protein sequence similarity. Such information can be used to improve human health or agriculture. The challenge lies in using a common language to transfer protein data annotations among different species of organisms. First step in achieving this huge challenge is producing a structured, precisely defined common vocabulary using Protein Ontology. The Protein Ontology described in this paper covers the sequence, structure and biological roles of Protein Complexes in any organism.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• BMB Reports
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• v.37 no.1
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• pp.93-106
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• 2004

The new complexity arising from the genome sequencing projects requires new comprehensive post-genomic strategies: advanced studies in regulatory mechanisms, application of new high-throughput technologies at a genome-wide scale, at the different levels of cellular complexity (genome, transcriptome, proteome and metabolome), efficient analysis of the results, and application of new bioinformatic methods in an integrative or systems biology perspective. This can be accomplished in studies with model organisms under controlled conditions. In this review a perspective of the favourable characteristics of yeast as a touchstone model in post-genomic research is presented. The state-of-the art, latest advances in the field and bottlenecks, new strategies, new regulatory mechanisms, applications (patents) and high-throughput technologies, most of them being developed and validated in yeast, are presented. The optimal characteristics of yeast as a well-defined system for comprehensive studies under controlled conditions makes it a perfect model to be used in integrative, 'systems biology' studies to get new insights into the mechanisms of regulation (regulatory networks) responsible of specific phenotypes under particular environmental conditions, to be applied to more complex organisms (e.g. plants, human).

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.56-61
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• 2001

Activated sludge processes are broadly used in the biological wastewater treatment processes. The activated sludge processes are complex systems because of the many factors such as the variation of influent flowrate and ingredients, the complexity of biological reactions, and the various operation conditions. The main motivation o this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system owing to the characteristic of wastewater, the change in influent flowrate, weather conditions, and so on. The mathematical model of ASP also includes the uncertainty which is a ignored or unconsidered factor from process designers. The ASP model based on Matlabⓡ/Simulinkⓡ is developed in this paper. And the model performance is examined by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data. The model tests derive steady-state results of 14 days. In this paper, fuzzy logic control approach is applied to handle DO concentrations. The fuzzy logic controller includes two inputs and one output to adjust air flowrate. The objective function for the optimization, in the implemented evolutionary strategy, is formed with focusing on improving the effluent quality and reducing the operating cost.

• Journal of Species Research
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• v.7 no.2
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• pp.123-134
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• 2018

A total of 22 bacterial strains belonging to the phylum Bacteroidetes were isolated primarily from aquatic environments such as seawater, freshwater, lagoon and tidal flat. One of these 22 strains was isolated from ginseng soil. Phylogenetic analyses based on 16S rRNA gene sequences revealed that 21 strains showed the high sequence similarities(${\geq}98.7%$) to the closest type strains and formed robust phylogenetic clades with closely related species in the phylum Bacteroidetes. One strain, which had been previously classified as Balneola vulgaris in the phylum Bacteroidetes, was identified as a member of the newly described phylum Rhodothermaeota. These strains had not been previously reported in Korea. Here, we report 21 species of 13 genera in the phylum Bacteroidetes and one species in the phylum Rhodothermaeota which were not reported in Korea. Morphological, biochemical, and physiological characteristics, isolation sources, and NIBR deposit numbers are described in the species descriptions.

• The Korean Journal of Ecology
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• v.21 no.6
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• pp.759-770
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• 1998

biotic indices scoring with the benthic macroinvertebrates were assessed as pollution monitoring tools in the north branch of the Han River system, Korea. We investigated the temporal variability of water quality at unpolluted, moderately polluted and heavily polluted sites using several biotic indices and assessed appropriate biological monitoring indices for lotic systems in Korea. The following biotic and chemical indices were employed in order to compare their applicability to the lotic systems : Trent Biotic Index (TBI), Chandler's Biotic Index-Average Score per Taxon (CBI-ASPT), Modified Biological Monitoring Working Party Score System-Average Score per Taxon (BMWP-ASPT), Hilsenhoff's biotic Index (BI) and Family-level Biotic Index (FBI) models for biotic analyses and National Sanitation foundation's Water Quality Index (NSFWQI) and comprehensive Chemical Pollution Index (Pb/n) for chemical analyses of water quality. Index and score values were compared with each other and with 24 water chemistry parameters. All biotic indices were significantly auto-correlated (p<0.001) and BI and FBI/ROK among them were highly correlated (r=0.84). BI and BMWP-ASPT models were also highly correlated with NSFWQI, while TBI values showed high correlation with the Pb/n. The BI and BMWP-ASPT were highly correlated with the most water chemistry parameters. We conclude that the BI model, which includes indicator species and abundance of taxa, is best suited for the bioassessment of lotic systems in Korea. For rapid field-based assessments, FBI/ROK and BMWP-ASPT models are also appropriate.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.830-836
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• 2005

Application of microarray technologies which monitor simultaneously the expression pattern of thousands of individual genes in different biological systems results in a tremendous increase of the amount of available gene expression data and have provided new insights into gene expression during drug development, within disease processes, and across species. There is a great need of data mining methods allowing straightforward interpretation, visualization and analysis of the relevant information contained in gene expression profiles. Specially, classifying biological samples into known classes or phenotypes is an important practical application for microarray gene expression profiles. Gene expression profiles obtained from tissue samples of patients thus allowcancer classification. In this research, molecular classification of microarray gene expression data is applied for multi-class cancer using computational biology such gene selection, principal component analysis and fuzzy clustering. The proposed method was applied to microarray data from leukemia patients; specifically, it was used to interpret the gene expression pattern and analyze the leukemia subtype whose expression profiles correlated with four cases of acute leukemia gene expression. A basic understanding of the microarray data analysis is also introduced.

• Korean Journal of Ecology and Environment
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• v.36 no.4 s.105
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• pp.463-466
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• 2003

This study was conducted to introduce the characteristics of the freshwater environment of Mulkol, considering that it is less known area about the ecosystem of the Tok Island. The salinity of freshwater in the Mulkol was less than 2.0 psu, while its periphytic algal biomass was thriving with 25.9 ${\mu}g\;chl-a/cm^2$. As for the nutrients in water, the content of $NH_4$ was higher than the rest of inorganic nitrogen components, and SRP and SRSi were much higher as 117.3 ${\mu}$g P/l and 4,104.6 ${\mu}$g Si/l respectively, than nitrogen components. Also, the ratio of N/P was found less than 1.0, revealing the condition that N was greatly limited. The high level of nutrient concentration and periphytic algal biomass at the Mulkol ecosystem could be explained as a result of natural pollution, but no full explanation was made in this study. It is a question that needs additional research in the future.