• Animal cells and systems
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• v.16 no.4
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• pp.289-294
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• 2012

Histone methylation has diverse functions including transcriptional regulation via its lysine or arginine residue methylation. Studies indicate that deregulation of histone methylation is linked to human cancers including leukemia. Histone H3K27 methyltrnasferase response element II binding protein (RE-IIBP), as a transcriptional repressor to target gene IL-5, interacts with HDAC and is over-expressed in leukemia patient samples. In this study, we have identified that hematopoiesis-related genes GATA1 and HOXA9 are down-regulated by RE-IIBP in K562 and 293T cells. Transient reporter analysis revealed that GATA1 transcription was repressed by RE-IIBP. On the other hand, HOXA9 and PBX-related homeobox gene MEIS1 was up-regulated by RE-IIBP. These results suggest that RE-IIBP might have a role in hematopoiesis or leukemogenesis by regulating the transcription of target genes, possibly via its H3K27 methyltransferase activity.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.83-92
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• 2005

This study if the first trial toward realizing a new methodology for vehicle re-identification based on heterogeneous sensor systems. A major interest of the author is how to effectively utilize information obtained from different sensors to derive accurate and reliable section travel times. The 'blade' sensor that is a newly developed sensor for capturing vehicle wheel information and the existing square loop sensor are employed to extract the inputs of the proposed vehicle re-identification algorithm. The fundamental idea of the algorithm developed in this study, which is so called 'anonumous vehicle re-identification,' it to match vehicle features obtained from both sensors. The results of the algorithm evaluation reveal that the proposed methodology could be successfully implemented in the field. The proposed methodology would be an invaluable tool for operating agencies in support of traffic monitoring systems and traveler information systems.

• The Plant Pathology Journal
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• v.40 no.5
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• pp.425-437
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• 2024

A large number of species in the genus Colletotrichum have been reported as causal agents of anthracnose on crops and wild plants in Korea. Many Colletotrichum isolates from the country preserved in the Korean Agricultural Culture Collection (KACC) were previously identified based on host plants and morphological characteristics, and it may lead to species misidentification. Thus, accurate fungal species identification using multilocus sequence analyses is essential for understanding disease epidemiology and disease management strategies. In this study, combined DNA sequence analyses of internal transcribed spacer, gapdh, chs-1, his3, act, tub2, and gs were applied to re-identify 27 Colletotrichum isolates in KACC. The phylogenetic analyses showed that the isolates resulted in 11 known species, they belong to the C. dematium species complex (C. hemerocallidis, C. jinshuiense, and C. spinaciae), the C. magnum complex (C. kaifengense and C. cf. ovatense), the C. orchidearum complex (C. cattleyicola, C. plurivorum, C. reniforme, and C. sojae) and the C. orbiculare complex (C. malvarum and C. orbiculare). Of them, C. cattleyicola, C. hemerocallidis, C. kaifengense, and C. reniforme were unrecorded species in Korea. In the view of host-fungus combinations, 10 combinations are newly reported in the world and 12 are new reports in Korea, although their pathogenicity on the host was not confirmed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.877-884
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• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.737-746
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• 2013

This research aim is to investigate the rate and pattern of re-using the four-digit personal identification numbers(PINs). 1313 types of PINs were observed by 224 students who took this author's classes from last 2006 to 2011 at A-university. Some students used PINs as few as 3-4 and as many as 12-13. The average is 5.86 per person. The rates of re-using PINs were calculated by each student. 87%(195/224) of students reused PINs and 64% of them reused with just only one type of PINs, 20% reused with 2 types, and about 3% reused with 3-4 types. With respect to PINs, 884 out of the total 1313 PINs were reused, that is around 64.3%. In a broad sense, a pair of slight modification of PINs were also observed, that is, new PINs were partly matched in position or size of numbers of previous PINs. And if the reuse rate falling under the slight modification of PINs, 10.4% is added, about 75% of the PINs were reused in a broad sense. The re-using rate of male students is higher than the one of female students. This paper's results may provide to make plan for hacks of passwords.

• Korean Journal of Construction Engineering and Management
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• v.4 no.2 s.14
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• pp.109-117
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• 2003

The construction project is largely exposed to much more risk events over the project life cycle due to its complexity and size than the other industries. Therefore, the construction risk management process to identify and response the risk events is not only performing acutely but also proceeding systematically. The risk identification phase in the risk management process is to identify various risk events and define its characteristics. At this phase, the risk identification system is very useful tool to identify every possible risk events in the project. This study shows some problems of the existing risk identification system and proposes the modified risk identification system based on the project phases and the contract bodies, and also suggests partial but more enough detailed risk checklists to be implemented in the actual risk identification phase than any other existing risk breakdown systems to be examined at this study.

• Safety and Health at Work
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• v.11 no.2
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• pp.127-135
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• 2020

A safe work environment is crucial in high-risk industries, such as construction refurbishment. Safety incidents caused by uncertainty and unexpected events in construction refurbishment systems are difficult to control using conventional safety management techniques. Resilience engineering (RE) is proposed as an alternative to traditional safety management approaches. It presents a successful safety management methodology designed to deal with uncertainty in high-risk work environments. Despite the fact that RE resides in the safety domain, there is no common set of RE indicators to measure and assess resilient in the work environment. The main aim of this research is to explore RE indicators that have been identified as important in developing and assessing the resilient work environment in high-risk industries, particularly in construction refurbishment. Indicators have been attained through a systematic literature review of research and scholarly articles published between the years 2004 and 2019. The literature review explored RE indicators in various industries. Descriptive analysis and co-occurrence-based network visualization were used for data analysis. The findings revealed 28 RE indicators in 11 different high-risk industries. The results show that the four commonly used indicators were: top-management commitment, awareness, learning, and flexibility, all of which have a strong relationship with RE. The findings of this study are useful for stakeholders when making decisions concerning the most important RE indicators in the context of their research or practice as this would avoid the ambiguity and disparity in the identification of RE indicators.

• Journal of Ecology and Environment
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• v.41 no.12
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• pp.345-350
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• 2017

Background: Ecological research often requires monitoring of a specific individual over an extended period of time. To enable non-invasive re-identification, consistent external marking is required. Treefrogs possess lateral lines for crypticity. While these patterns decrease predator detection, they also are individual specific patterns. In this study, we tested the use of lateral lines in captive and wild populations of Dryophytes japonicus as natural markers for individual identification. For the purpose of the study, the results of visual and software assisted identifications were compared. Results: In normalized laboratory conditions, a visual individual identification method resulted in a 0.00 rate of false-negative identification (RFNI) and a 0.0068 rate of false-positive identification (RFPI), whereas Wild-ID resulted in RFNI = 0.25 and RFNI = 0.00. In the wild, female and male data sets were tested. For both data sets, visual identification resulted in RFNI and RFPI of 0.00, whereas the RFNI was 1.0 and RFPI was 0.00 with Wild-ID. Wild-ID did not perform as well as visual identification methods and had low scores for matching photographs. The matching scores were significantly correlated with the continuity of the type of camera used in the field. Conclusions: We provide clear methodological guidelines for photographic identification of D. japonicus using their lateral lines. We also recommend the use of Wild-ID as a supplemental tool rather the principal identification method when analyzing large datasets.

• Phonetics and Speech Sciences
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• v.1 no.1
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• pp.63-67
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• 2009

In this paper, in order to protect music copyrights, we propose a music identification system which is scalable to the number of pieces of registered music and robust to signal-level variations of registered music. For its implementation, we define the new concepts of 'music word' and 'music phoneme' as recognition units to construct 'music acoustic models'. Then, with these concepts, we apply the HMM-based framework used in continuous speech recognition to identify the music. Each music file is transformed to a sequence of 39-dimensional vectors. This sequence of vectors is represented as ordered states with Gaussian mixtures. These ordered states are trained using Baum-Welch re-estimation method. Music files with a suspicious copyright are also transformed to a sequence of vectors. Then, the most probable music file is identified using Viterbi algorithm through the music identification network. We implemented a music identification system for 1,000 MP3 music files and tested this system with variations in terms of MP3 bit rate and music speed rate. Our proposed music identification system demonstrates robust performance to signal variations. In addition, scalability of this system is independent of the number of registered music files, since our system is based on HMM method.

• Structural Engineering and Mechanics
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• v.41 no.1
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• pp.25-41
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• 2012

Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a scheme for crack identification based on a Kriging surrogate model is proposed. A modified rectangular grid (MRG) is introduced to move some sample points lying on the boundary into the internal design region, which will provide more useful information for the construction of Kriging model. The initial Kriging model is then constructed by samples of varying crack parameters (locations and sizes) and their corresponding modal frequencies. For identifying crack parameters, a robust stochastic particle swarm optimization (SPSO) algorithm is used to find the global optimal solution beyond the constructed Kriging model. To improve the accuracy of surrogate model, the finite element (FE) analysis soft ANSYS is employed to deal with the re-meshing problem during surrogate model updating. Specially, a simple method for crack number identification is proposed by finding the maximum probability factor. Finally, numerical simulations and experimental research are performed to assess the effectiveness and noise immunity of this proposed scheme.