• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.91-98
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• 2022

In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.169-190
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• 2023

Uzbekistan, one of the top five cotton-producing countries in the world, primarily focuses its textile and fashion industry on raw cotton exports and the sewing industry. For Uzbekistan to achieve high added value, it is essential for the textile and fashion industry, which is currently at the CMT(cut, make, and trim) stage, to upgrade to OEM (original equipment manufacturing), ODM (original design manufacturing), and OBM (original brand manufacturing). South Korea recognizes Uzbekistan as a potential manufacturing base and trading partner and has invested Official Development Assistance (ODA) funds for the development of Uzbekistan's textiles and apparel sector. This study aims to evaluate Uzbekistan's fashion higher education in the context of global competitiveness and measure the need and prospects for education ODA from the Korean government in this field. Comprehensive investigations, including surveys of academics, industry experts, and government officials, in-depth interviews, and focus group interviews, were conducted to understand Uzbekistan's current fashion education environment. According to the research results, despite the textile and fashion sectors playing a pivotal role in the Uzbek economy, there is room for improvement in the curricula and teaching and learning methods of the fashion higher education programs. This study holds significance as foundational data for establishing education ODA strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1857-1862
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• 2013

Dermal fibroblasts produce the many components of the extracellular matrix (ECM) that are needed to maintain connective tissue integrity and repair tissue injuries. This study investigated the effects of Areca catechu extract (ACE) on dermal fibroblast cell activation. Cultured human dermal fibroblasts were treated with ACE, and then ECM production was determined by ELISA, Western blot and RT-PCR. ACE significantly accelerated the production of type 1 collagen, fibronectin, and transforming growth factor (TGF)-${\beta}1$ by ELISA and type 1 collagen by Western blot assay. ACE also increased the gene expression of COL1A1, TGF-${\beta}1$, keratinocyte growth factor (KGF) and insulin growth factor (IGF)-1. These results suggest that ACE has the potential to stimulate ECM production and that it might be suitable for maintaining skin texture.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.40 no.4
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• pp.413-421
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• 2014

Corticotropin-releasing factor (CRF) is involved in the stress response and there is increasing evidence that stress influences skin disease such as hair loss. In cultured human hair follicles, CRF inhibits hair shaft elongation, induces premature regression and promotes the apoptosis of hair matrix keratinocytes. We investigated whether CRF influences the dermal papilla cells (DPC) that play pivotal roles in hair growth and cycling. Human DPCs were treated with CRF, adrenocorticotropic hormone (ACTH) and cortisol, key stress hormones along the hypothalamic-pituitary -adrenal (HPA) axis for 1-24 h. Interestingly, CRF modulated the expression of cytokines related to hair growth (KGF, Wnt5a, $TGF{\beta}-2$, Nexin) and increased cAMP production in cultured DPCs. CRF receptors were down-regulated by negative feedback systems. Pretreatment of CRF receptor antagonists or protein kinase A (PKA) inhibitor prevented the CRF-induced modulation. Since the CRF induces proopiomelanocortin (POMC) expression through the cAMP/PKA pathway, we analyzed POMC mRNA. CRF stimulated POMC expression in cultured human DPCs, yet we were unable to detect ACTH levels by western blot. These results indicate that CRF operates within DPCs through CRF receptors along the classical CRF signaling pathway and CRF receptor antagonists could serve as potential therapeutic and cosmetic agents for stress-induced hair loss.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.355-362
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• 2012

Remaining useful life(RUL) prediction of a system is important in the prognostics field since it is directly linked with safety and maintenance scheduling. In the physics-based prognostics, accurately estimated model parameters can predict the remaining useful life exactly. It, however, is not a simple task to estimate the model parameters because most real system have multivariate model parameters, also they are correlated each other. This paper presents representative methods to estimate model parameters in the physics-based prognostics and discusses the difference between three methods; the particle filter method(PF), the overall Bayesian method(OBM), and the sequential Bayesian method(SBM). The three methods are based on the same theoretical background, the Bayesian estimation technique, but the methods are distinguished from each other in the sampling methods or uncertainty analysis process. Therefore, a simple physical model as an easy task and the Paris model for crack growth problem are used to discuss the difference between the three methods, and the performance of each method evaluated by using established prognostics metrics is compared.