• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.948-948
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• 2005

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.949-949
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• 2005

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.950-950
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• 2005

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.951-951
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• 2005

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.975-975
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• 2005

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.90-96
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• 2023

Securing large amounts of training data in deep learning neural networks, including convolutional neural networks, is of importance for avoiding overfitting phenomenon or for the excellent performance. However, securing labeled training data in deep learning neural networks is very limited in reality. To overcome this, several augmentation methods have been proposed in the literature to generate an additional large amount of training data through transformation or manipulation of the already acquired traing data. However, unlike training data such as images and texts, it is barely to find an augmentation method in the literature that additionally generates bio-signal training data for convolutional neural network based human activity recognition. Thus, this study proposes a simple but effective augmentation method of bio-signal training data for convolutional neural network based human activity recognition. The usefulness of the proposed augmentation method is validated by showing that human activity is recognized with high accuracy by convolutional neural network trained with its augmented bio-signal training data.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.3.1-3.4
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• 2010

In the present research, we assessed the utility of the structural information of drugs for predicting human in vivo intrinsic clearance from in vitro intrinsic clearance data obtained by human hepatic microsome experiment. To compare with the observed intrinsic clearance, human intrinsic clearance values for 51 drugs were estimated by the classical methods using in vivo-in vitro scale-up and by the new methods using the in vitro experimental data and selected molecular descriptors of drugs by the forward selection technique together. The results showed that taking consideration of molecular descriptors into prediction from in vitro experimental data could improve the prediction accuracy. The in vitro experiment is very useful when the data can estimate in vivo data accurately since it can reduce the cost of drug development. Improvement of prediction accuracy in the present approach can enhance the utility of in vitro data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.43-52
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• 2011

In this paper, we propose the architecture of the policy-based emergency bio data transmission for the smart healthcare service. the medical staff can quickly and accurately monitor the emergency bio data of the remote patient through the proposed architecture. The proposed system consists of three parts: IEEE 11073-based agents and managers performing the aggregation function and transmission function of the bio data; the emergency management server performing the converting function between IEEE 11073 and HL7 and auto-diagnosis function of the policy-based; HL7 medical system based on HL7. Finally, by implementing the proposed system, we shows that the aggregation of the bio data and management of the emergency bio data in the smart healthcare service are possible.

• Mycobiology
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• v.49 no.6
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• pp.582-588
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• 2021

The interaction of mating pheromone and pheromone receptor from the B mating-type locus is the first step in the activation of the mushroom mating signal transduction pathway. The B mating-type locus of Lentinula edodes is composed of Bα and Bβ subloci, each of which contains genes for mating pheromone and pheromone receptor. Allelic variations in both subloci generate multiple B mating-types through which L. edodes maintains genetic diversity. In addition to the B mating-type locus, our genomic sequence analysis revealed the presence of a novel chromosomal locus 43.3 kb away from the B mating-type locus, containing genes for a pair of mating pheromones (PHBN1 and PHBN2) and a pheromone receptor (RCBN). The new locus (Bα-N) was homologous to the Bα sublocus, but unlike the multiallelic Bα sublocus, it was highly conserved across the wild and cultivated strains. The interactions of RcbN with various mating pheromones from the B and Bα-N mating-type loci were investigated using yeast model that replaced endogenous yeast mating pheromone receptor STE2 with RCBN. The yeast mating signal transduction pathway was only activated in the presence of PHBN1 or PHBN2 in the RcbN producing yeast, indicating that RcbN interacts with self-pheromones (PHBN1 and PHBN2), not with pheromones from the B mating-type locus. The biological function of the Bα-N locus was suggested to control the expression of A mating-type genes, as evidenced by the increased expression of two A-genes HD1 and HD2 upon the treatment of synthetic PHBN1 and PHBN2 peptides to the monokaryotic strain of L. edodes.

• Journal of Veterinary Science
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• v.25 no.5
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• pp.59.1-59.10
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• 2024

Importance: Despite advancements in herd management, feeding, and pharmaceutical interventions, neonatal calf diarrhea (NCD) remains a major global health concern. Bacteria, viruses, and parasites are the major contributors to NCD. Although several pathogens have been identified in the Republic of Korea (ROK), the etiological agents of numerous NCD cases have not been identified. Objective: To identify, for the first time, the prevalence and impact of Boosepivirus (BooV) on calf diarrhea in the ROK. Methods: Here, the unknown cause of calf diarrhea was determined using metagenomics We then explored the prevalence of certain pathogens, including BooV, that cause NCD. Seventy diarrheal fecal samples from Hanwoo (Bos taurus coreanae) calves were analyzed using reverse transcriptase and quantitative real-time polymerase chain reaction for pathogen detection and BooV isolate sequencing. Results: The complete genome of BooV was detected from unknown causes of calf diarrhea. And also, BooV was the most frequently detected pathogen (35.7%) among 8 pathogens in 70 diarrheic feces from Hanwoo calves. Co-infection analyses indicated that most BooV-positive samples were solely infected with BooV, indicating its significance in NCD in the ROK. All isolates were classified as BooV B in phylogenetic analysis. Conclusions and Relevance: This is the first study to determine the prevalence and molecular characteristics of BooV in calf diarrhea in the ROK, highlighting the potential importance of BooV as a causative agent of calf diarrhea and highlighting the need for further research on its epidemiology and pathogenicity.