• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.269-276
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• 2016

Internet of Things (IoT) is based on wireless networks being able to connect things and people on a large scale. In the IoT environment, reliable broadcast plays an important role to distribute data to a large number of devices. Energy harvesting from a surrounding environment is a key technique to achieve a sustainable IoT network. In IoT networks, a problem of transmission errors and energy shortage should be mitigated for reliable broadcast. In this paper, we propose an energy-efficient and reliable broadcast method to consider packet errors and energy consumption in the environment where a large number of nodes are connected. The proposed scheme can improve data restoration probability by up to 15% and reduce energy consumption by up to 17%.

• Computers and Concrete
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• v.23 no.6
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• pp.433-444
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• 2019

As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.345-356
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• 2012

Road pavement requires repetitive maintenance works to maintain satisfactory service level to the public. However, the repetitive maintenance works upon deteriorated pavement structure make negative effects to deterioration speed. It often leads to inefficient use of limited budget. For that reason, the pavements require reconstruction work to recover their original performance. Recently, construction demands in the Korean national highway have already been reached to maximum level, and the aged pavements start to demand much more reconstruction works. However, in the real world, road agencies have often been confused when they determine maintenance design for such aged road sections due to budget constraint. It is because there is no reliable long-term maintenance strategy that supports their decision making. To support their decision making, this paper aimed to suggest the best maintenance strategy considering changing process of pavement performance by repetitive maintenance works. As an analysis method, probability distribution and hazard function to estimate the life expectancy were adopted, and then the results were used for long-term life cycle cost analysis with deterministic or Monte-Carlo method under various scenarios. As an empirical study, the Korean national highway data that has long-maintenance history data since 1986 has been applied. Last, this paper considered quality assurance of maintenance work to improve maintenance quality. These could be important information as a part of long-term maintenance strategy of pavement.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.8
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• pp.15-26
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• 2011

In this paper, we present a new beamforming scheme for a downlink of multiuser multiple-input multipleoutput (MIMO) communication systems. Recently, a block-diagonalization (BD) algorithm has been proposed for the multiuser MIMO downlink where both a base station and each user have multiple antennas. However, the BD algorithm is not efficient when the number of supported streams per user is smaller than that of receive antennas. Since the BD method utilizes the space based on the channel matrix without considering the receive combining, the degree of freedom for beamforming cannot be fully exploited at the transmitter. In this paper, we optimize the receive beamforming vector under a zero forcing (ZF) constraint, where all inter-user interference is driven to zero. We propose an efficient algorithm to find the optimum receive vector by an iterative procedure. The proposed algorithm requires two phase values feedforward information for the receive combining vector. Also, we present another algorithm which needs only one phase value by using a decomposition of the complex general unitary matrix. Simulation results show that the proposed beamforming scheme outperforms the conventional BD algorithm in terms of error probability and obtains the diversity enhancement by utilizing the degree of freedom at the base station.

• Journal of Labour Economics
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• v.26 no.3
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• pp.149-179
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• 2003

This study is analysing the factors determining individuals' behavior of selecting self-employment not only at the micro-level but also at the macro-level to put a particular emphasis on the financial constraint and unemployment rate representing business cycle. The data used in this study are "Korean Labor and Income Panal Study" of the Korea Labor Institute and "Economically Active Population Survey" of National Statistical Office. The main findings are as follows. First, human capital such as educational attainment and job experience has positive effects on male's selection of self-employment. The effects of job experience, however, changed negative for female's selection of self-employment. Second, real estate is significantly enhancing the selection probabilities of employer selection while the income from financial assets has negative effects. Third, entrepreneurial culture and environment are also raising the self-employment selection probability. Lastly, the regional unemployment rate representing the business cycle has positive effects on the self-employment selection after the financial crisis in 1997 both at the micro and macro level. Moreover, the coefficient of regional unemployment rate has changed positive in the structural model of self-employment selection controlling for selection bias and income opportunities, which means that individual's behavior of self-employment selection is rather complex when accounting for the uncertainties of income opportunities and diverse characteristics of self-employment workforce.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.169-176
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• 2018

In this paper, we consider duty-cycled wireless sensor networks (WSNs) in which sensor nodes are periodically dormant in order to reduce energy consumption. In such networks, as the duty cycle interval increases, the energy consumption decreases. However, a higher duty cycle interval leads to the increase in the end-to-end (E2E) delay. Many applications of WSNs are delay-sensitive and require packets to be delivered from the sensr nodes to the sink with delay requirements. Most of existing studies focus on only reducing the E2E delay, rather than considering the delay bound requirement, which makes hard to achieve the balanced performance between E2E delay and energy consumption. A few study that considered delay bound requirement require time synchronization between neighboring nodes or a specific distribution of deployed nodes. In order to address limitations of existing works, we propose a duty-cycle scheduling algorithm that aims to achieve low energy consumption, while satisfying the delay requirements. To that end, we first estimate the probability distribution for the E2E delay. Then, by using the obtained distribution we determine the maximal duty cycle interval that still satisfies the delay constraint. Simulation results show that the proposed design can satisfy the given delay bound requirements while achieving low energy consumption.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.4
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• pp.1-9
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• 2014

With the development of quantum computer, the development of the quantum-inspired search method applying the features of quantum mechanics and its application to engineering problems have emerged as one of the most interesting research topics. This algorithm stores information by using quantum-bit superposed basically by zero and one and approaches optional values through the quantum-gate operation. In this process, it can easily keep the balance between the two features of exploration and exploitation, and continually accumulates evolutionary information. This makes it differentiated from the existing search methods and estimated as a new algorithm as well. Thus, this study is to suggest a new minimum weight design technique by applying quantum-inspired search method into structural optimization of planar truss. In its mathematical model for optimum design, cost function is minimum weight and constraint function consists of the displacement and stress. To trace the accumulative process and gathering process of evolutionary information, the examples of 10-bar planar truss and 17-bar planar truss are chosen as the numerical examples, and their results are analyzed. The result of the structural optimized design in the numerical examples shows it has better result in minimum weight design, compared to those of the other existing search methods. It is also observed that more accurate optional values can be acquired as the result by accumulating evolutionary information. Besides, terminal condition is easily caught by representing Quantum-bit in probability.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.531-540
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• 2022

In this paper, we present an algorithm that identifies artillery type and rapidly predicts the impact point based on the IMM filter. The ballistic trajectory equation is used as a system model, and three models with different ballistic coefficient values are used. Acceleration was divided into three components of gravity, air resistance, and lift. And lift acceleration was added as a new state variable. The kinematic condition that the velocity vector and lift acceleration are perpendicular was used as a pseudo-measurement value. The impact point was predicted based on the state variable estimated through the IMM filter and the ballistic coefficient of the model with the highest mode probability. Instead of the commonly used Runge-Kutta numerical integration for impact point prediction, a semi-analytic method was used to predict impact point with a small amount of calculation. Finally, a state variable initialization method using the least-square method was proposed. An integrated algorithm including artillery type identification, impact point prediction and initialization was presented, and the validity of the proposed method was verified through simulation.