• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.103-103
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• 2000

In this paper to cope with the reduction of products life-cycle as the variety of products along with the various demands of consumers, a virtual simulator is developed to make the changeover of manufacturing line efficient to embody a virtual simulation similar to a real manufacturing line. The developed virtual simulator can design a layout of a factory and make the time scheduling. Every factory has one simulator so that one product can be manufactured in the factories to use them as virtual factories. We suggest a scheme that heightens the agility to the diversity of manufacturing models by making the information of manufacturing lines and products models to be shared. The developed unit simulator can construct a proper virtual manufacturing line along with the required process of products using several kinds of operator and work cell. A user with the simulator can utilize an interface that makes one to manage the separate task process for each manu(acturing module, change operator components and work cells, and easily teach tasks of each task module. The developed simulator was made for users convenience by Microsoft Visual C++ 6.0 that can develop a program supplying graphic user interface environment and by OpenGL of the Silicon Graphics as a graphic library to embody 3D graphic environment. Also, we show that the simulator can be used efficiently for the agile manufacturing by the communication among the factories being linked by TCP/IP and a hybrid database system made by a hierarchical model and a relational model being developed to standardize the data information.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.16-28
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• 2018

Although physiological and ecological characteristics of cyanobacteria have been studied extensively for decades, unknown areas still remain greater than the already known. Recently, the development of omics techniques based on molecular biology has made it possible to view the ecosystem from a new and holistic perspective. The molecular mechanism of toxin production is being widely investigated, by comparative genomics and the transcriptomic studies. Biological interaction between bacteria and cyanobacteria is also explored: how their interactions and genetic biodiversity change depending on seasons and environmental factors, and how these interactions finally affect each component of ecosystem. Bioinformatics techniques have combined with ecoinformatics and omics data, enabling us to understand the underlying complex mechanisms of ecosystems. Particularly omics started to provide a whole picture of biological responses, occurring from all layers of hierarchical processes from DNA to metabolites. The expectation is growing further that algal blooms could be controlled more effectively in the near future. And an important insight for the successful bloom control would come from a novel blueprint drawn by omics studies.

• Journal of Ginseng Research
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• v.38 no.1
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• pp.52-58
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• 2014

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2016.11a
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• pp.122.2-122.2
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• 2016

Surface topographical cues has been highlighted to control the fate of neural stem cells (NSCs). Herein we developed a hierarchically patterned substrate (HPS) platform for regulating NSC differentiation. The HPS induced cytoskeleton alignment and highly activated focal adhesion in hNSCs as indicated by enhanced expression of focal adhesion proteins such as focal adhesion kinase (FAK) and vinculin. hNSCs cultured on HPS exhibited enhanced neuronal differentiation compared to flat group. We also developed a graphene oxide (GO)-based hierarchically patterned substrates (GPS) that promote focal adhesion formation and neuronal differentiation of hNSCs. Enhanced focal adhesion and differentiation of hNSCs on the HPS was reversed by blocking the ${\beta}1$ integrin binding and mechanotransduction-associated signals including Rho-associated protein kinase (ROCK) and extracellular-regulated kinase (ERK) pathway, which may suggest a potential mechanism of beneficial effects of HPS. In addition, hNSCs on the HPS differentiated into functional neurons exhibiting sodium currents and action potentials as confirmed by whole cell patch-clamping analysis. The hierarchical topography can direct differentiation of NSCs towards functional neurons, and therefore would be an important element for the design of functional biomaterials for neural tissue regeneration applications.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.39-51
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• 2012

Cluster analysis has proven to be a useful tool for investigating the association structure among genes and samples in a microarray data set. We applied several cluster validation measures to evaluate the performance of clustering algorithms for analyzing microarray gene expression data, including hierarchical clustering, K-means, PAM, SOM and model-based clustering. The available validation measures fall into the three general categories of internal, stability and biological. The performance of clustering algorithms is evaluated using simulated and SRBCT microarray data. Our results from simulated data show that nearly every methods have good results with same result as the number of classes in the original data. For the SRBCT data the best choice for the number of clusters is less clear than the simulated data. It appeared that PAM, SOM, model-based method showed similar results to simulated data under Silhouette with of internal measure as well as PAM and model-based method under biological measure, while model-based clustering has the best value of stability measure.

• The KIPS Transactions:PartC
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• v.12C no.3 s.99
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• pp.419-428
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• 2005

This paper divides domains into the intra, inter domain according to the mobile node's movement and .proposes the Fast RSVP algorithm on the HMIPv6. It is done to advance reservation using L2 beacon signal when MN is located to overlapped cell area. In case of intra-region handoff, the advance reservation is reserved at the nearest common router and In case of inter-region handoff, it is done to advance reservation through the other site MAP's QA(QoS Agent) to the AR and optimize CN's path. Because of using the bandwidth efficiently and switching the data path quickly, the proposal algorithm minimizes the service disruption by data routing.

• Molecules and Cells
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• v.44 no.9
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• pp.627-636
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• 2021

The three-dimensional organization of chromatin and its time-dependent changes greatly affect virtually every cellular function, especially DNA replication, genome maintenance, transcription regulation, and cell differentiation. Sequencing-based techniques such as ChIP-seq, ATAC-seq, and Hi-C provide abundant information on how genomic elements are coupled with regulatory proteins and functionally organized into hierarchical domains through their interactions. However, visualizing the time-dependent changes of such organization in individual cells remains challenging. Recent developments of CRISPR systems for site-specific fluorescent labeling of genomic loci have provided promising strategies for visualizing chromatin dynamics in live cells. However, there are several limiting factors, including background signals, off-target binding of CRISPR, and rapid photobleaching of the fluorophores, requiring a large number of target-bound CRISPR complexes to reliably distinguish the target-specific foci from the background. Various modifications have been engineered into the CRISPR system to enhance the signal-to-background ratio and signal longevity to detect target foci more reliably and efficiently, and to reduce the required target size. In this review, we comprehensively compare the performances of recently developed CRISPR designs for improved visualization of genomic loci in terms of the reliability of target detection, the ability to detect small repeat loci, and the allowed time of live tracking. Longer observation of genomic loci allows the detailed identification of the dynamic characteristics of chromatin. The diffusion properties of chromatin found in recent studies are reviewed, which provide suggestions for the underlying biological processes.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.1
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• pp.38-48
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• 2019

Objective: In this study, the transcriptome profile of cow experiencing miscarriage during peri-implantation was investigated. Methods: Total transcriptomes were checked by RNA sequencing, and the analyzed by bioinformatics methods, the differentially expressed genes (DEGs) were analysed with hierarchical clustering and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. Results: The results suggested that serum progesterone levels were significantly decreased in cows that miscarried as compared to the pregnant cows at 18, 21, 33, 39, and 51 days after artificial insemination. The RNA sequencing results suggested that 32, 176, 5, 10, and 2 DEGs were identified in the pregnant cows and miscarried cows at 18, 21, 33, 39, and 51 d after artificial insemination. And 15, 101, 1, 2, and 2 DEGs were upregulated, and 17, 74, 4, and 8 DEGs were downregulated in the cows in the pregnant and miscarriage groups, respectively at 18, 21, 33, and 39, but no gene was downregulated at 51 d after artificial insemination. These DEGs were distributed to 13, 20, 3, 6, and 20 pathways, and some pathway essential for pregnancy, such as cell adhesion molecules, tumor necrosis factor signaling pathway and PI3K-Akt signaling pathway. Conclusion: This analysis has identified several genes and related pathways crucial for pregnancy and miscarriage in cows, as well as these genes supply molecular markers to predict the miscarriage in cows.

• Clinical and Experimental Pediatrics
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• v.64 no.7
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• pp.355-363
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• 2021

Background: Nephrotic syndrome (NS) is a common renal disorder in children attributed to podocyte injury. However, children with the same diagnosis have markedly variable treatment responses, clinical courses, and outcomes, suggesting molecular heterogeneity. Purpose: This study aimed to explore the molecular responses of podocytes to nephrotic plasma to identify specific genes and signaling pathways differentiating various clinical NS groups as well as biological processes that drive injury in normal podocytes. Methods: Transcriptome profiles from immortalized human podocyte cell line exposed to the plasma of 8 subjects (steroid-sensitive nephrotic syndrome [SSNS], n=4; steroid-resistant nephrotic syndrome [SRNS], n=2; and healthy adult individuals [control], n=2) were generated using microarray analysis. Results: Unsupervised hierarchical clustering of global gene expression data was broadly correlated with the clinical classification of NS. Differential gene expression (DGE) analysis of diseased groups (SSNS or SRNS) versus healthy controls identified 105 genes (58 up-regulated, 47 down-regulated) in SSNS and 139 genes (78 up-regulated, 61 down-regulated) in SRNS with 55 common to SSNS and SRNS, while the rest were unique (50 in SSNS, 84 genes in SRNS). Pathway analysis of the significant (P≤0.05, -1≤ log2 FC ≥1) differentially expressed genes identified the transforming growth factor-β and Janus kinase-signal transducer and activator of transcription pathways to be involved in both SSNS and SRNS. DGE analysis of SSNS versus SRNS identified 2,350 genes with values of P≤0.05, and a heatmap of corresponding expression values of these genes in each subject showed clear differences in SSNS and SRNS. Conclusion: Our study observations indicate that, although podocyte injury follows similar pathways in different clinical subgroups, the pathways are modulated differently as evidenced by the heatmap. Such transcriptome profiling with a larger cohort can stratify patients into intrinsic subtypes and provide insight into the molecular mechanisms of podocyte injury.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.