• International journal of advanced smart convergence
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• v.10 no.3
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• pp.122-130
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• 2021

This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2001.06a
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• pp.96-96
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• 2001

• The Korea Genome Conference
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• 2004.07a
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• pp.49.2-49.2
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• 2004

• Development and Reproduction
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• v.18 no.1
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• pp.1-11
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• 2014

Early growth response 1 (Egr1) is a zinc-finger transcription factor to direct second-wave gene expression leading to cell growth, differentiation and/or apoptosis. While it is well-known that Egr1 controls transcription of an array of targets in various cell types, downstream target gene(s) whose transcription is regulated by Egr1 in the uterus has not been identified yet. Thus, we have tried to identify a list of potential target genes of Egr1 in the uterus by performing multi-step in silico promoter analyses. Analyses of mRNA microarray data provided a cohort of genes (102 genes) which were differentially expressed (DEGs) in the uterus between Egr1(+/+) and Egr1(-/-) mice. In mice, the frequency of putative EGR1 binding sites (EBS) in the promoter of DEGs is significantly higher than that of randomly selected non-DEGs, although it is not correlated with expression levels of DEGs. Furthermore, EBS are considerably enriched within -500 bp of DEG's promoters. Comparative analyses for EBS of DEGs with the promoters of other species provided power to distinguish DEGs with higher probability as EGR1 direct target genes. Eleven EBS in the promoters of 9 genes among analyzed DEGs are conserved between various species including human. In conclusion, this study provides evidence that analyses of mRNA expression profiles followed by two-step in silico analyses could provide a list of putative Egr1 direct target genes in the uterus where any known direct target genes are yet reported for further functional studies.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.70-74
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• 1989

To track the target trajectory with maneuvers, unknown maneuvering inputs must be estimated. To do this the direct estimation algorithm using generalized least square technique is developed based on the procedure of failure detection and identification(FDI) theory. Through the simulation using maneuvering target scenario, tracking performance and efficiency of the algorithm developed here are investigated.

• Biomolecules & Therapeutics
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• v.22 no.5
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• pp.371-383
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• 2014

The nematode Caenorhabditis elegans (C. elegans) offers a unique opportunity for biological and basic medical researches due to its genetic tractability and well-defined developmental lineage. It also provides an exceptional model for genetic, molecular, and cellular analysis of human disease-related genes. Recently, C. elegans has been used as an ideal model for the identification and functional analysis of drugs (or small-molecules) in vivo. In this review, we describe conserved oncogenic signaling pathways (Wnt, Notch, and Ras) and their potential roles in the development of cancer stem cells. During C. elegans germline development, these signaling pathways regulate multiple cellular processes such as germline stem cell niche specification, germline stem cell maintenance, and germ cell fate specification. Therefore, the aberrant regulations of these signaling pathways can cause either loss of germline stem cells or overproliferation of a specific cell type, resulting in sterility. This sterility phenotype allows us to identify drugs that can modulate the oncogenic signaling pathways directly or indirectly through a high-throughput screening. Current in vivo or in vitro screening methods are largely focused on the specific core signaling components. However, this phenotype-based screening will identify drugs that possibly target upstream or downstream of core signaling pathways as well as exclude toxic effects. Although phenotype-based drug screening is ideal, the identification of drug targets is a major challenge. We here introduce a new technique, called Drug Affinity Responsive Target Stability (DARTS). This innovative method is able to identify the target of the identified drug. Importantly, signaling pathways and their regulators in C. elegans are highly conserved in most vertebrates, including humans. Therefore, C. elegans will provide a great opportunity to identify therapeutic drugs and their targets, as well as to understand mechanisms underlying the formation of cancer.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.186-191
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• 2006

The perception of English labial consonants was investigated via experiment where 40 Korean EFL learners identified nonwords with the target labial consonants [p, b, f, v] in 4 different prosodic locations: initial onset position, intervocalic position before stress, intervocalic position after stress, and final coda position. The overall result showed that the proportion of perception accuracy of the target consonants was rather low, amounting to only 55%. There was also a positional effect since the accuracy rates for perceiving the four target consonants differed by position. Specifically, the average accuracy rate of the target consonant identification was higher in intervocalic position before stress (70%) and initial onset position (67%) than in intervocalic position after stress (45%) and final coda position (36%). Further, the accuracy rate for [f] is was high in all prosodic locations except intervocalic position after stress. The perception patterns were accounted for by the markedness and perceptual factors in conjunction with stress location.

• Journal of Korean Association for Spatial Structures
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• v.3 no.4 s.10
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• pp.53-58
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• 2003

In order to control seismic responses of building structures effectively and stably, it is very important to estimate the dynamic characteristics of target structure exactly based on input-output signal data. In this paper, it is shown that Subspace Identification Method is able to be applied effectively to system identification of building structures. To verify the efficiency of Subspace Identification Method, the vibration experiments were conducted on a specimen structure which is a 5-storied building structure model consisted of H-shaped steel beam, and the simulated seismic responses of the identified structure model were compared with the observed ones under the same excitation. It was observed that the experimental results coincided with the analyzed ones proposed in this paper.