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Extracting spatial features of fNIRS signal using a graph representation
Minseok Seo,Eugene Jeong,Kyung-Soo Kim 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Due to its solid ability to extract local spatial features from image, convolutional neural network (CNN) has been used frequently to extract spatial features from functional near infra-red spectroscopy (fNIRS) signal. To apply CNN to multi-channel fNIRS signal, the signal has to be converted to an image. However, 2-dimensional convolution is effective only when adjacent pixels share connectivity. In order to reduce the convolution of features from unrelated channels and leave correlated channels together, graph convolution network based on functional connectivity (FC) is proposed. Spatial features extracted from different types of graphs were compared using support vector machine (SVM). Feature extracted from functional connectivity-based graph showed better performance in classifying unseen data, while 2-D convolution like methods showed sign of overfitting.
Characterizing Milk Production Related Genes in Holstein Using RNA-seq
Seo, Minseok,Lee, Hyun-Jeong,Kim, Kwondo,Caetano-Anolles, Kelsey,Jeong, Jin Young,Park, Sungkwon,Oh, Young Kyun,Cho, Seoae,Kim, Heebal Asian Australasian Association of Animal Productio 2016 Animal Bioscience Vol.29 No.3
Although the chemical, physical, and nutritional properties of bovine milk have been extensively studied, only a few studies have attempted to characterize milk-synthesizing genes using RNA-seq data. RNA-seq data was collected from 21 Holstein samples, along with group information about milk production ability; milk yield; and protein, fat, and solid contents. Meta-analysis was employed in order to generally characterize genes related to milk production. In addition, we attempted to investigate the relationship between milk related traits, parity, and lactation period. We observed that milk fat is highly correlated with lactation period; this result indicates that this effect should be considered in the model in order to accurately detect milk production related genes. By employing our developed model, 271 genes were significantly (false discovery rate [FDR] adjusted p-value<0.1) detected as milk production related differentially expressed genes. Of these genes, five (albumin, nitric oxide synthase 3, RNA-binding region (RNP1, RRM) containing 3, secreted and transmembrane 1, and serine palmitoyltransferase, small subunit B) were technically validated using quantitative real-time polymerase chain reaction (qRT-PCR) in order to check the accuracy of RNA-seq analysis. Finally, 83 gene ontology biological processes including several blood vessel and mammary gland development related terms, were significantly detected using DAVID gene-set enrichment analysis. From these results, we observed that detected milk production related genes are highly enriched in the circulation system process and mammary gland related biological functions. In addition, we observed that detected genes including caveolin 1, mammary serum amyloid A3.2, lingual antimicrobial peptide, cathelicidin 4 (CATHL4), cathelicidin 6 (CATHL6) have been reported in other species as milk production related gene. For this reason, we concluded that our detected 271 genes would be strong candidates for determining milk production.
Minseok Seo,Eugene Jeong,Kyung-Soo Kim 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
Electroencephalography (EEG) and functional near infra-red spectroscopy (fNIRS) are popular noninvasive methods for brain-computer interfaces (BCI), due to the simplicity and portability of the systems. Although the systems have gone through great progress in development, a satisfiable intention estimation has not yet been developed, and is being tackled by many neural activity researchers. This paper will utilize EEG and FNIRS to estimate the intentions of its users, whether the user is resting, or moving their right or left hand via CNN and SVM.
Mass printing of colored natural patterns on Al plate by roll imprinting and thin film deposition
Seo, Minseok,Lee, Joo-Yul,Rha, Jong-Joo,Kim, Man,Lee, Myeongkyu Elsevier 2020 Journal of materials processing technology Vol.278 No.-
<P><B>Abstract</B></P> <P>Metal surfaces finished in color patterns are useful and attractive for both practical and artistic purposes. Although the surface of metals can be patterned by diverse methods including computerized-numerical-control machining, laser-direct surface structuring, and droplet printing, these serial processes are not suitable for the massive manufacturing of complex patterns with variant feature sizes. In this work, we present a continuous roll-imprinting process as a large-area, high-throughput method for producing arbitrary surface patterns on Al. The surface patterns of natural objects such as silk, leather, and paper are replicated via Ni electroplating, and the electroplated Ni replica mold is used as the imprinting roller to transfer the original natural pattern onto an Al plate. The conformity of the imprinted pattern to the original pattern is 80―85 %. Surface-patterned Al plates are also colorized by coating a metal-dielectric double layer, where the top metal layer adjusts the amount of light incident into the underlying dielectric film, strengthening the interference effect. Diverse colors are generated by varying the thicknesses of the coating layers. The colors obtained via experiments agree well with the results predicted using finite-difference time-domain simulation. This study provides a fast and scalable route for producing colored surface patterns on metals and may find various applications ranging from surface decoration and visual arts to product identification and anti-counterfeiting.</P>
Vivid structural colors produced on stainless steel
Seo, Minseok,Lee, Myeongkyu Elsevier 2018 Acta materialia Vol.159 No.-
<P><B>Abstract</B></P> <P>As the esthetic functions of metals have attracted increasing attention, their coloration is a significant issue in scientific and technological aspects. We here demonstrate that vivid structural colors can be produced on stainless steel. The structure consists of a SU-8 layer coated on the surface of bulk stainless steel that has a one-dimensional texture of 500 nm period. Polarization-dependent, diverse colors are produced simply by changing the thickness of the dielectric overlayer. The colors result from the surface plasmon resonance and guided mode resonance of incident light, which occur on the metal surface and inside the dielectric layer, respectively. Simulation based on the finite-difference time-domain method supports the experimental results, showing that the layer thickness influences the characteristic wavelengths of both resonances and the resulting colors. Color image patterns are also printable on the surface of stainless steel by irradiating a solution-coated SU-8 layer with a pulsed ultraviolet laser beam. The final thickness of the photopolymeric SU-8 layer is locally controlled by adjusting laser fluence. The current study provides a simple route to produce diverse structural colors on metals and may find many applications including surface decoration, product identification, and anti-counterfeiting.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>