• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.53-61
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• 2008

Consider a typical wireless sensor network in which stem nodes form the backbone network of mesh topology while each stem node together with leaf nodes in its vicinity forms a subnetwork of star topology. In such a wireless sensor network, we must heed the following when we design a MAC scheme supporting the packet delivery from a leaf node to a stem node. First, leaf nodes are usually battery-powered and it is difficult to change or recharge their batteries. Secondly, a wireless sensor network is often deployed to collect and update data periodically. Late delivery of a data segment by a sensor node causes the sink node to defer data processing and the data segment itself to be obsolete. Thirdly, extensive signaling is extremely limited and complex computation is hardly supported. Taking account of these facts, a MAC scheme must be able to save energy and support timeliness in packet delivery while being simple and robust as well. In this paper, we propose a version of ALOHA as a MAC scheme for a wireless sensor network. While conserving the simplicity and robustness of the original version of ALOHA, the proposed version of ALOHA possesses a distinctive feature that a sensor node decides between stop and continuation prior to each delivery attempt for a packet. Such a decision needs a stopping rule and we suggest a Bayes stopping rule. Note that a Bayes stopping rule minimizes the Bayes risk which reflects the energy, timeliness and throughput losses. Also, a Bayes stopping rule is practical since a sensor node makes a decision only using its own history of delivery attempt results and the prior information about the failure in delivery attempt. Numerical examples confirm that the proposed version of ALOHA employing a Bayes stopping rule is a useful MAC scheme in the severe environment of wireless sensor network.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.747-752
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• 2006

In this paper, the adaptive fuzzy sliding mode controller with two systems is designed. The existing sliding mode controller used to $approximation{\^{u}}(t)$ with discrete sgn function and sat function for keeping the state trajectories on the sliding surface[1]. The proposed controller decrease the disturbance for uncertain control gain and This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems ate used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties ate demonstrated. Futhermore, fuzzy tuning improve tracking abilities by changing some sliding conditions. In the traditional sliding mode control, ${\eta}$ is a positive constant. The increase of ${\eta}$ has led to a significant decrease in the rise time. However, this has resulted in higher overshoot. Therefore the proposed ${\eta}$ tuning AFSMC improve the performances, so that the controller can track the trajectories faster and more exactly than ordinary controller. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.513-524
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• 2022

Recently, detecting damages of civil infrastructures from digital images using deep learning technology became a very popular research topic. In order to adapt those methodologies to the field, it is essential to explain robustness of deep learning models. Our research points out that the existing pixel-based deep learning model evaluation metrics are not sufficient for detecting cracks since cracks have linear appearance, and proposes a new evaluation methodology to explain crack segmentation deep learning model more rationally. Specifically, we design, implement and validate a methodology to generate tolerance buffer alongside skeletonized ground truth data and prediction results to consider overall similarity of topology of the ground truth and the prediction rather than pixel-wise accuracy. We could overcome over-estimation or under-estimation problem of crack segmentation model evaluation through using our methodology, and we expect that our methodology can explain crack segmentation deep learning models better.

• Computers and Concrete
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• v.31 no.3
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• pp.267-276
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• 2023

The main purpose of the current research is to develop an efficient two variables trigonometric shear deformation beam theory to investigate the buckling behavior of symmetric and non-symmetric functionally graded carbon nanotubes reinforced composite (FG-CNTRC) beam resting on an elastic foundation with various boundary conditions. The proposed theory obviates the use to shear correction factors as it satisfies the parabolic variation of through-thickness shear stress distribution. The composite beam is made of a polymeric matrix reinforced by aligned and distributed single-walled carbon nanotubes (SWCNTs) with different patterns of reinforcement. The material properties of the FG-CNTRC beam are estimated by using the rule of mixture. The governing equilibrium equations are solved by using new analytical solutions based on the Galerkin method. The robustness and accuracy of the proposed analytical model are demonstrated by comparing its results with those available by other researchers in the existing literature. Moreover, a comprehensive parametric study is presented and discussed in detail to show the effects of CNTs volume fraction, distribution patterns of CNTs, boundary conditions, length-to-thickness ratio, and spring constant factors on the buckling response of FG-CNTRC beam. Some new referential results are reported for the first time, which will serve as a benchmark for future research.

• Asia Marketing Journal
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• v.15 no.3
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• pp.53-77
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• 2013

As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.

• Journal of Korea Trade
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• v.27 no.5
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• pp.1-22
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• 2023

Purpose - Southeast Asia has been the focus of Korea's foreign investment. Korea has been helping developing countries in Southeast Asia achieve economic growth and win-win cooperation through capital exports. FDI is an important channel for technology diffusion. However, the impact of FDI on the bias of technological progress in the host country is dependent on the host country's own endowment structure and capital-labor factor substitution elasticity. Therefore, the central issue of this paper is to accurately evaluate the impact of Korea's FDI to the four Southeast Asian countries in various industries on their bias of technological progress. Design/methodology - The paper uses macroeconomic data for Korea and four East Asian countries to estimate capital-labor factor elasticities of substitution using nonlinear, seemingly uncorrelated regressions (NLSUR). Then, the biased technological change index (BTCI) is calculated for each country. Finally, panel data analysis is used to explore the impact of Korean FDI in various industries in the four Southeast Asian countries on their own directed technological progress, and a robustness test is conducted. Findings - There is a substitution relationship between capital and labor factors based on their elasticity in Korea, Singapore and the Philippines. There is a complementary relationship between capital and labor factors in Indonesia and Malaysia. According to the BTCI, there is a trend toward labor-biased technological progress in all countries. Korean investments in manufacturing, wholesale and retail trade in the host country trigger capital-biased technological change in the host country; investments in the finance, insurance and information and communication sectors trigger labor-biased technological change. In addition, this paper also confirms that directed technological progress can enable cross-country transmission. Originality/value - The innovation of this paper lies in three aspects. First, we estimate the BTCI for five countries and explore the trend and situation of directed technological progress in each country from each country's own perspective. Second, we explore the impact of Korean FDI in the host country on the bias to its technological progress at the industry level. Second, we explore the impact of Korean FDI in various industries in the four Southeast Asian countries on the four countries' own directed technological progress from a national perspective. Finally, we propose corresponding countermeasures for technological progress from the perspective of inverse factor endowment. These innovative points not only expand the understanding of technological progress and cross-country technology transfer in East Asia but also provide practical references for policy-makers and business operators.

• Clean Technology
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• v.24 no.2
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• pp.127-134
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• 2018

To reduce the environmental pollution by $NO_x$ from ship engine, International maritime organization (IMO) announced Tier III regulation, which is the emmision regulation of ship's exhaust gas in Emission control area (ECA). Selective catalytic reduction (SCR) process is the most commercial $De-NO_x$ system in order to meet the requirement of Tier III regulation. In generally, commercial ceramic honeycomb SCR catalyst has been installed in SCR reactor inside marine vessel engine. However, the ceramic honeycomb SCR catalyst has some serious issues such as low strength and easy destroution at high velocity of exhaust gas from the marine engine. For these reasons, we design to metallic structured catalyst in order to compensate the defects of the ceramic honeycomb catalyst for applying marine SCR system. Especially, metallic structured catalyst has many advantages such as robustness, compactness, lightness, and high thermal conductivity etc. In this study, in order to support catalyst on metal substrate, coating slurry is prepared by changing binder. we successfully fabricate the metallic structured catalyst with strong adhesion by coating, drying, and calcination process. And we carry out the SCR performance and durability such as sonication and dropping test for the prepared samples. The MFC01 shows above 95% of $NO_x$ conversion and much more robust and more stable compared to the commercial honeycomb catalyst. Based on the evaluation of characterization and performance test, we confirm that the proposed metallic structured catalyst in this study has high efficient and durability. Therefore, we suggest that the metallic structured catalyst may be a good alternative as a new type of SCR catalyst for marine SCR system.