• Journal of the Korean Chemical Society
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• v.46 no.2
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• pp.157-163
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• 2002

To identify RNA motifs interacting with $tRNA^{Val}$, a SELEX(Systematic Evolution of Ligands by Exponential Enrichment) was applied. Random DNA library which contains a region of ran-domized 48-mer oligonucleotide flanked by conserved sequ ence primers was transcribed into RNA pool using T7 RNA polymerase and RNA aptamers were selected with $tRNA^{Val}$ -immobilized affinity column through 14 rounds of SELEX. Some of the resulting aptamers contained a consensus sequence similar to the sequence in the loop regions of three rRNAs; C43GAAC47 sequence of 5S rRNA, G1491AAGU1495, G1379UUCC1383 sequence of 16S rRNA and C1064UUAG1068, G2110UGUA2114, C2480GACGG2485, A2600CAGU2604 sequence of 23S rRNA. These results suggest that $tRNA^{Val}$ can interact with 5S rRNA, 16S rRNA and 23S rRNA with variety in ribosome.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.8-14
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• 2008

There are two a approaches for the Cognitive Radio(CR) development. One is 'Full CR', which Joseph Mitola III proposed, and another is 'Spectrum CR', which is currently being standardized. The target approach of this paper is the latter and we develop a Cognitive Engine(CE) and simulated a channel set management(CSM), which is a core function of CE. The Channel set management evaluates channel quality and Incumbent User(IU) vacancy possibility and classifies the channel set, which is performed by using channel state history. Especially, a very important function for the channel set management is a channel state prediction and this paper proposed a Hidden Markov Model(HMM) based channel state prediction and a method for increasing performance. Also, we applied the proposed method into our simulator and simulated channel state prediction. Through the simulation, we verified as we applied our proposed scheme, the performance of channel state prediction gets better and through comparing with RS and SS, we verified the HMM based Channel state prediction is better.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.115-123
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• 2011

Distribution system loss minimization re-configuration is 0-1 planning problem, and the number of combinations requiring searches is extremely large when dealing with typical system scales. For this reason, the application of a genetic algorithm (GA) seems a tractive to solve this problem. Although Genetic algorithms are a type of random number search method, they incorporate a multi-point search feature and are therefore superior to one-point search techniques. The incorporate of GAs for solving large combinational problem has received wide attention. Further, parallel searching can be performed and the optimal solution is more easily reach ed. In this paper, for improving GA convergence characteristics in the distribution system loss minimization re-configuration problem, a chromosome "Limited Life" concept is introduced. Briefly, considering the population homogenization and genetic drift problems, natural selection is achieved by providing this new concept, in addition to natural selection by fitness. This is possible because individuals in a population have an age value. Simulation were carried out using a model system to check this method's validity.

• YAKHAK HOEJI
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• v.57 no.2
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• pp.125-131
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• 2013

Biologically active peptides, including growth factors and cytokines, participate in various biological processes in human skin. They could provide a great advantage of maintaining healthy skin. Many peptide growth factors like epidermal growth factor (EGF) and human growth hormone (hGH) have been used in cosmetic formulations. The delivery of peptide growth factors across the Stratum corneum, however, seems not sufficient because of their physical properties such as high molecular weight and hydrophilicity. So increasing the penetration of growth factors of interest into skin would be a major concern for ensuring their maximum biological efficacy. In this study, we have identified several skin penetration-enhancing peptides which facilitate delivery of growth factors, when fused at N-terminus of the target protein, into skin. For efficient and rapid screening, we constructed a skin-penetrating assay system using Franz cell and porcine skin. Next, we carried out phage display screening using M-13 bacteriophage with random 12 -amino acid library on its coat protein P3 on that system. After several selection rounds, peptide sequences facilitate the penetration of phages through the porcine skin were identified from a large population of phages. We found that phages with the most potent peptide (S3-2, NGSLNTHLAPIL) could penetrate the porcine skin eight times more than those with control peptide (12 mino acids scrambled peptide). Furthermore, growth factors conjugated with S3-2 peptide penetrate porcine skin three to five times efficiently than non-conjugated growth factors. In conclusion, our data shows that the skin penetration-enhancing peptide we have characterized could increase the delivery of growth factors and is useful for cosmeceutical application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1811-1819
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• 2013

In this paper, we carried out a study on how to find an appropriate helper node for cooperative communications, the role of which is very import to enhance system throughput of wireless communication system. The busy tone cooperative MAC (BT-COMAC) protocol proposed in this paper is a new cooperative MAC protocol with a reactive helper node scheme and maximizes the benefits of existing schemes while making up for their shortcomings. We conducted performance evaluation of this new protocol using computer simulation experiment. System throughput in bps and channel access delay are utilized as performance measures. We used a random way point mobility model where every communication node moves independently one another, and slow fading channel where every communication node decided its transmission rate with received power basis. Numerical results show that the new MAC protocol enhances system throughput as much as 15% of the existing scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.943-948
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• 2018

In this paper, we propose a hybrid approach of combining $A^*$ and Genetic algorithm in the path search problem. In $A^*$, the cost from a start node to the intermediate node is optimized in principle but the path from that intermediate node to the goal node is generated and tested based on the cumulated cost and the next node in a priority queue is chosen to be tested. In that process, we adopt the genetic algorithm principle in that the group of nodes to generate the next node from an intermediate node is tested by its fitness function. Top two nodes are selected to use crossover or mutation operation to generate the next generation. If generated nodes are qualified, those nodes are inserted to the priority queue. The proposed method is compared with the original sequential selection and the random selection of the next searching path in $A^*$ algorithm and the result verifies the superiority of the proposed method.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.464-464
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• 2010

A few years ago, for maintaining high stability and production yield of production equipment in a semiconductor fab, on-line monitoring of wafers is required, so that semiconductor manufacturers are investigating a software based process controlling scheme known as virtual metrology (VM). As semiconductor technology develops, the cost of fabrication tool/facility has reached its budget limit, and reducing metrology cost can obviously help to keep semiconductor manufacturing cost. By virtue of prediction, VM enables wafer-level control (or even down to site level), reduces within-lot variability, and increases process capability, $C_{pk}$. In this research, we have practiced VM on $SiO_2$ etch rate with optical emission spectroscopy(OES) data acquired in-situ while the process parameters are simultaneously correlated. To build process model of $SiO_2$ via, we first performed a series of etch runs according to the statistically designed experiment, called design of experiments (DOE). OES data are automatically logged with etch rate, and some OES spectra that correlated with $SiO_2$ etch rate is selected. Once the feature of OES data is selected, the preprocessed OES spectra is then used for in-situ sensor based VM modeling. ICP-RIE using 葰.56MHz, manufactured by Plasmart, Ltd. is employed in this experiment, and single fiber-optic attached for in-situ OES data acquisition. Before applying statistical feature selection, empirical feature selection of OES data is initially performed in order not to fall in a statistical misleading, which causes from random noise or large variation of insignificantly correlated responses with process itself. The accuracy of the proposed VM is still need to be developed in order to successfully replace the existing metrology, but it is no doubt that VM can support engineering decision of "go or not go" in the consecutive processing step.

• BMB Reports
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• v.54 no.3
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• pp.176-181
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• 2021

Bcl-x, a member of the Bcl-2 family, plays a key role in apoptosis. Alternative splicing of Bcl-x pre-mRNA through alternative 5' splice-site selection produces an anti-apoptotic mRNA isoform that includes exon 2b and a pro-apoptotic Bcl-x mRNA isoform that excludes exon 2b. Here we used Bcl-x minigene and identified SRSF2 and SRSF6 as two regulatory factors of 5' splice-site selection of Bcl-x pre-mRNA. We selected binding clusters closer to 5' splice-sites from multiple potential binding sites of SRSF2 and SRSF6 to perform loss of functions analysis through site-directed mutagenesis. Our results demonstrated that these mutations did not abolish regulatory functions of SRSF2 or SRSF6, indicating that a single binding motif or a cluster was not a functional target of these proteins in Bcl-x pre-mRNA splicing. Random deletion mutagenesis did not disrupt the role of SRSF2 and SRSF6. Importantly, mutagenesis of 5' splice-site to a conserved or a weaker score demonstrated that the weaker strength of the target 5' splice-site or higher strength of the other 5' splice-site strength limited the role of SRSF2 and SRSF6 in 5' splice-site activation.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.