• Smart Structures and Systems
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• 제22권5호
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• 한국군사과학기술학회지
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• 제25권2호
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• pp.177-186
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• 2022

A network QoS model for the joint integrated C4I structure was proposed for the integration of network infrastructure and network operations(NetOps) for NCOE. Detailed QoS requirements process of the joint integrated C4I systems are needs in the Multi-Domain Operation Environment(MDOE). A process is proposed for identifying QoS requirements and establishing in the MDOE using JMT(Joint Mission Thread) reference architecture and solution architecture. Mission analysis identify JCOAs(Joint Critical Operational Activities) and related activities based on JMT & System architecture's OVs, and Information analysis identify QoS attributes using System architecture's SVs. Identifying QoS attributes will be registered at PPS Registry by pre-regulated process, and will be set-up by NetOps. MDOE QoS requirement Process will support efficiently MUM-T and smart defense platform users under the future uncertain battlefield circumstances.

• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.255-262
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• 2023

The purpose of this study was to clarify the concept of LGBT cultural competence in nurses. This study used Walker and Avant's 8 steps of conceptual analysis. The specific steps are: (1) selecting the concept, (2) selecting the purpose of concept analysis, (3) identifying the scope of concept use, (4) identifying the determinant attributes of the concept, (5) presenting model cases, (6) additional cases of the concept (boundary cases, opposite cases, and related cases), (7) identifying antecedents and consequences, and (8) presenting empirical evidence. As a result, five attributes of nurses' LGBT cultural competence were identified in the final 12 articles: cultural experience and cultural acceptance, cultural knowledge, cultural attitude and awareness, and cultural skills. Antecedents included diversification of society, heteronormative healthcare environment, continuing education and training, intercultural understanding, and open-mindedness. Outcomes of cultural competence were identified as reducing LGBT health inequalities and providing quality care. In conclusion, this study contributes to providing a basis for improving the quality of nursing care by providing more culturally appropriate care to the target population through conceptual analysis and understanding of nurses' LGBT cultural competence. Furthermore, it is necessary to continue research on the development of tools to measure nurses' LGBT cultural competence and the development of nursing intervention programmes that can be applied in nursing practice.

• BMB Reports
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• 제37권1호
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• pp.107-113
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• 2004

Since the completion of the genome project of the nematode C. elegans in 1998, functional genomic approaches have been applied to elucidate the gene and protein networks in this model organism. The recent completion of the whole genome of C. briggsae, a close sister species of C. elegans, now makes it possible to employ the comparative genomic approaches for identifying regulatory mechanisms that are conserved in these species and to make more precise annotation of the predicted genes. RNA interference (RNAi) screenings in C. elegans have been performed to screen the whole genome for the genes whose mutations give rise to specific phenotypes of interest. RNAi screens can also be used to identify genes that act genetically together with a gene of interest. Microarray experiments have been very useful in identifying genes that exhibit co-regulated expression profiles in given genetic or environmental conditions. Proteomic approaches also can be applied to the nematode, just as in other species whose genomes are known. With all these functional genomic tools, genetics will still remain an important tool for gene function studies in the post genome era. New breakthroughs in C. elegans biology, such as establishing a feasible gene knockout method, immortalized cell lines, or identifying viruses that can be used as vectors for introducing exogenous gene constructs into the worms, will augment the usage of this small organism for genome-wide biology.

• 대한수학회논문집
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• 제21권3호
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• pp.533-541
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• 2006

We consider a autoregressive moving average process of order p and q with Markov switching coefficients and find sufficient conditions for irreducibility of the process. Identifying small sets is also examined.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.479-485
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• 2003

The influence of observations on the Wilks' lambda test of a linear hypothesis in multivariate regression is investigated using the local influence method. The perturbation scheme of case-weights is considered. A numerical example is given to show the effectiveness of the local influence method in identifying the influential observations.

• 한국경영과학회지
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• 제18권3호
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• pp.79-100
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• 1993

This paper proposes an idea of reverse modeling that analyzes LP models and then converts them into an object-oriented model repository. The process of reverse modeling consists of (1) identifying and analyzing source models by meta processor, (2) model decomposition and generalization to scan the models and divide them into model components, and (3) deriving model selection rules from the components by rule generator. Through the process, we can extract reusable model components and build a model base with model selectioon rules. Examples with models created by SML and MODLER modeling languages are given to illustrate the methods. The model base management capabilities provided by reverse modeling can increase the reusabioity of current modeling tools.

• 응용통계연구
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• 제25권3호
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• pp.503-512
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• 2012

Detecting outliers in a linear regression model eventually fails when similar observations are classified differently in a sequential process. In such circumstances, identifying clusters and applying certain methods to the clustered data can prevent a failure to detect outliers and is computationally efficient due to the reduction of data. In this paper, we suggest to implement a clustering procedure for this purpose and provide examples that illustrate the suggested procedure applied to the Hadi-Simonoff (1993) method, reverse Hadi-Simonoff method, and Gentleman-Wilk (1975) method.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 2003년도 정기총회 및 학술발표회
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• pp.77-77
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• 2003

Gene expression in a cell is regulated by mutual activations or repressions between genes. Identifying the gene regulation network will be one of the most important research topics in the post genomic era. We propose a linear dynamic model of gene regulation for the yeast cell cycle. A small gene network consisting of about 40 genes is reconstructed from the analysis of micro-array gene expression data of yeast S. cerevisiae published by P. Spellman et al. We show that the network construction is consistent with the result of the hierarchical cluster analysis.

• 인터넷정보학회논문지
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• 제19권4호
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• pp.35-44
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• 2018

Monitoring through Synthesis Aperture Radar (SAR) is responsible for marine safety from floating icebergs. However, there are limits to distinguishing between icebergs and ships in SAR images. Convolutional Neural Network (CNN) is used to distinguish the iceberg from the ship. The goal of this paper is to increase the accuracy of identifying icebergs from SAR images. The metrics for performance evaluation uses the log loss. The two-layer CNN model proposed in research of C.Bentes et al.[1] is used as a benchmark model and compared with the four-layer CNN model using data augmentation. Finally, the performance of the final CNN model using the VGG-16 pre-trained model is compared with the previous model. This paper shows how to improve the benchmark model and propose the final CNN model.