• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.203-211
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• 2015

The implanted telemetry system provides the monitoring of species while they move within their cages. Species monitored include mice, rats, rabbits, dogs, pigs, primates, sheep, horses, cattle, and others. A miniature transmitter implanted in each animal measures one or more parameters. Parameters measured include arterial pressure, intra-pleural pressure, left ventricular pressure, intra-ocular pressure, bladder pressure, ECG, EMG, EEG, EOG, temperature, activity, and other parameters and transmits the data via radio frequency signals to a nearby receiver. Every conventional dedicated transmitter contains one or more sensors, cpu and battery. Due to the expected life of battery, the measuring time is limited. To overcome these problems, electromagnetic inductive coupling based wireless power transmission technology using multiple transmit coils were proposed. Each coil having different active area are driven by the coil driver. In this research, parallel resonance based coil driver was proposed. In addition, the device to detect where the receiver is positioned was proposed. From the experiments we show how to determine the driving condition of coil driver.

• Journal of the East Asian Society of Dietary Life
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• v.15 no.4
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• pp.475-482
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• 2005

As Korea has approached the aging society, older Koreans have become an important force in restaurant sales today. To succeed with this silver market, it is important for restaurant managers to know who they are and which factor influence the older Koreans' eating-out decision making process. The purpose of this study was to investigate the effect of the elderly consumers financial independency on restaurant selection process. Data were collected from 178 older consumers above 55 years old and analyzed using the descriptive statistic analysis, MANOVA, and one-way ANOVA. The results showed that the elderly consumers financial independency significantly influenced the decision making process in determining where they eat out Significant differences were found between high income group and low income group in the Problem Recognition Step(Wilks' Lambda=0.776, F=3.796), Information Search Step(Wilks' Lambda=0.779, F=2.959), Alternative Evaluation Step (I :Wilks' Lambda=0.835, F=1.748/ II :Wilks' Lambda=0.764, F=3.212), and Purchase Decision Step(Wilks' Lambda=0.849, F=2.412), except the Post-Purchase Behavior(Wilks' Lambda=0.933, F=1.179). The more financially independent older consumers were, the more directly they were involved in the eating out decision making process. Older consumers with higher income and more personal property were likely to 'propose to eat out by themselves'(F=10.986), to obtain restaurant information from the 'printed materials'(F=9.707), to consider 'convenient location' as most important factor when they eat out(F=5.594), and to go to 'family restaurant'(F=7.067), 'Japanese restaurant'(F=7.391) and 'fine dining restaurants'(F-=6.382). In conclusion, we found that the elderly consumers financial independency did influence the eating-out decision making process. Considering that older Korean will become a financially independent consumer and will be eating away from home more often, food service operations should actively position themselves for this market and develop the market-driven menus and services to meet their needs and expectations.

• The Korean Journal of Physiology and Pharmacology
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• v.19 no.5
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• pp.441-449
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• 2015

Flavonoids are plant pigments that have been demonstrated to exert various pharmacological effects including anti-cancer, anti-diabetic, anti-atherosclerotic, anti-bacterial, and anti-inflammatory activities. However, the molecular mechanisms in terms of exact target proteins of flavonoids are not fully elucidated yet. In this study, we aimed to evaluate the anti-inflammatory mechanism of scutellarein (SCT), a flavonoid isolated from Erigeron breviscapus, Clerodendrum phlomidis and Oroxylum indicum Vent that have been traditionally used to treat various inflammatory diseases in China and Brazil. For this purpose, a nitric oxide (NO) assay, polymerase chain reaction (PCR), nuclear fractionation, immunoblot analysis, a kinase assay, and an overexpression strategy were employed. Scutellarein significantly inhibited NO production in a dose-dependent manner and reduced the mRNA expression levels of inducible NO synthase (iNOS) and tumor necrosis factor (TNF)-${\alpha}$ in lipopolysaccharide (LPS)-activated RAW264.7 cells. In addition, SCT also dampened nuclear factor (NF)-${\kappa}B$-driven expression of a luciferase reporter gene upon transfection of a TIR-domain-containing adapter-inducing interferon-${\beta}$ (TRIF) construct into Human embryonic kidney 293 (HEK 293) cells; similarly, NF-${\kappa}B$ nuclear translocation was inhibited by SCT. Moreover, the phosphorylation levels of various upstream signaling enzymes involved in NF-${\kappa}B$ activation were decreased by SCT treatment in LPS-treated RAW264.7 cells. Finally, SCT strongly inhibited Src kinase activity and also inhibited the autophosphorylation of overexpressed Src. Therefore, our data suggest that SCT can block the inflammatory response by directly inhibiting Src kinase activity linked to NF-${\kappa}B$ activation.

• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.53-61
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• 2014

Previous studies reveal the need for a tool to cost estimation of building design in early design stages. This paper proposes an internal finishes cost model tool to address this need. The tool allows users to evaluate the functionality, economics and quality of finishes concurrently with high-rise building design. Lack of information in the early stages of the project enables a relatively accurate estimates of work to raise up. Measurements are automatically extracted from simple design information and profile driven estimates are revised in real-time. The data model uses a flexible unit rate system that can easily be extended to other estimate dimensions such as mix-use building surcharge rate estimation. The approach illustrated in this paper is applicable to BIM tool conceptual estimation that support for massing purposes other than the one chosen for this study.

• Coupled systems mechanics
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• v.8 no.1
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• pp.71-93
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• 2019

Finite element simulations of solid mechanics problems often involve the use of Non-Confirming Meshes (NCM) to increase accuracy in capturing nonlinear behavior, including damage and plasticity, in part of a solid domain without an undue increase in computational costs. In the presence of material nonlinearity and plasticity, higher-order variables are often needed to capture nonlinear behavior and material history on non-conforming interfaces. The most popular formulations for coupling non-conforming meshes are dual methods that involve the interpolation of a traction field on the interface. These methods are subject to the Ladyzhenskaya-Babuska-Brezzi (LBB) stability condition, and are therefore limited in their implementation with the higher-order elements needed to capture nonlinear material behavior. Alternatively, the enriched discontinuous Galerkin approach (EDGA) (Haikal and Hjelmstad 2010) is a primal method that provides higher order kinematic fields on the interface, and in which interface tractions are computed from local finite element estimates, therefore facilitating its implementation with nonlinear material models. The inclusion of higher-order interface variables, however, presents the issue of preserving material history at integration points when a increase in integration order is needed. In this study, the enriched discontinuous Galerkin approach (EDGA) is extended to the case of small-deformation plasticity. An interface-driven Gauss-Kronrod integration rule is proposed to enable adaptive enrichment on the interface while preserving history-dependent material data at existing integration points. The method is implemented using classical J2 plasticity theory as well as the pressure-dependent Drucker-Prager material model. We show that an efficient treatment of interface variables can improve algorithmic performance and provide a consistent approach for coupling non-conforming meshes in inelasticity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.62-68
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• 2023

An aerial relay system utilizing an unmanned aerial vehicle(UAV) or drone is addressed for event-driven operations such as temporary communication services for disaster affected area, military and first responder support. UAV relay system (URS) targets to provide a reliable communication service to a remote user equipment or an operator, therefore, a fast UAV placement to guarantee a minimum quality of service(QoS) is important when an operation is requested. Researches on UAV utilization in communication systems mostly target to derive the optimal position of UAV to maximize the performance, however, fast deployment of UAV is much more important than optimal placement under emergency situations. To this end, this paper derives the feasible area for UAV placement, investigates the effect of performance requirements on that area, and suggests UAV placement to certainly guarantee the performance requirements. Simulation results demonstrate that the feasible area derived in this paper matches that obtained by an exhaustive search.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.305-310
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• 2024

With the emergence of generative AI, a new era of coexistence with humanity has begun. The vast data-driven learning capabilities of AI are being utilized in various industries to achieve a level of productivity distinct from human learning. However, AI also manifests societal phenomena such as technophobia. This study aims to analyze collaborative AI models based on an understanding of AI and identify areas within the jewelry industry where these models can be applied. The utilization of collaborative AI models can lead to the acceleration of idea development, enhancement of design capabilities, increased productivity, and the internalization of multimodal functions. Ultimately, AI should be used as a collaborative tool from a utilitarian perspective, which requires a proactive, human-centric mindset. This research proposes collaborative AI strategies for the jewelry business, hoping to enhance the industry's competitiveness.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of the Korean GEO-environmental Society
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• v.9 no.5
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• pp.45-52
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• 2008

The present study has extended OpenSees, which is an open-source software framework DOS program for developing applications to idealize geotechnical and structural problems, for the static analysis of axial load capacity and settlement of single piles in MS Windows environment. The Windows version of OpenSees as improved by this study has enhanced the DOS version from a general purpose software program to a special purpose program for driven and bored pile analysis with additional features of pre-processing and post-processing and a user friendly graphical interface. The method used in the load capacity analysis is the numerical methods based on load transfer functions combined with finite elements. The use of empirical nonlinear T-z and Q-z load transfer curves to model soil-pile interaction in skin friction and end bearing, respectively, has been shown to capture the nonlinear soil-pile response under settlement due to load. Validation studies have shown the static load capacity and settlement predictions implemented in this study are in fair agreement with reference data from the static loading tests.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.1-13
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• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.