• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.41-52
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• 2010

Even though REITs (Real Estate Investment Trusts) are listed on the stock market, REITs have characteristics that allow them to invest in real estate and financing for real estate development. Therefore REITs is related with stock market and construction business and real estate business. Using time-series analysis, this study analyzed REITs in relation to construction businesses, real estate businesses, and the stock market, and derived influence factor of REITs. We used the VAR (vector auto-regression) and the VECM (vector error correction model) for the time-series analysis. This study classified three steps in the analysis. First, we performed the time-series analysis between REITs and construction KOSPI(The Korea composite stock price index) and the result showed that construction KOSPI influenced REITs. Second, we analyzed the relationship between REITs and construction commencement area of the coincident construction composite index, office index and housing price index in real estate business indexes. REITs and the housing price index influence each other, although there is no causal relationship between them. Third, we analyzed the relationship between REITs and the construction permit area of the leading construction composite index. The construction permit area is influenced by REITs, although there is no causal relationship between these two indexes, REITs influenced the stock market and housing price indexes and the construction permit area of the leading composite index in construction businesses, but exerted a relatively small influence in construction starts coincident with the composite office indexes in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1263-1274
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• 2021

In online competitive social networks, each user can be influenced by different competing influencers and consequently chooses different products. But their interest may change over time and may have swings between different products. The existing influence spreading models seldom take into account the time-related shifts. This paper proposes a minimum cost influence maximization algorithm based on the competitive transition probability. In the model, we set a one-dimensional vector for each node to record the probability that the node chooses each different competing influencer. In the process of propagation, the influence maximization on Competitive Linear Threshold (IMCLT) spreading model is proposed. This model does not determine by which competing influencer the node is activated, but sets different weights for all competing influencers. In the process of spreading, we select the seed nodes according to the cost function of each node, and evaluate the final influence based on the competitive transition probability. Experiments on different datasets show that the proposed minimum cost competitive influence maximization algorithm based on IMCLT spreading model has excellent performance compared with other methods, and the computational performance of the method is also reasonable.

• Computers and Concrete
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• v.25 no.6
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• pp.565-574
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• 2020

Over the years, several machine learning approaches have been proposed and utilized to create a prediction model for the high-performance concrete (HPC) slump flow. Despite HPC is a highly complex material, predicting its pattern is a rather ambitious process. Hence, choosing and applying the correct method remain a crucial task. Like some other problems, prediction of HPC slump flow suffers from abnormal attributes which might both have an influence on prediction accuracy and increases variance. In recent years, different studies are proposed to optimize the prediction accuracy for HPC slump flow. However, more state-of-the-art regression algorithms can be implemented to create a better model. This study focuses on several methods with different mathematical backgrounds to get the best possible results. Four well-known algorithms Support Vector Regression, M5P Trees, Random Forest, and MLPReg are implemented with optimum parameters as base learners. Also, redundant features are examined to better understand both how ingredients influence on prediction models and whether possible to achieve acceptable results with a few components. Based on the findings, the MLPReg algorithm with optimum parameters gives better results than others in terms of commonly used statistical error evaluation metrics. Besides, chosen algorithms can give rather accurate results using just a few attributes of a slump flow dataset.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.209-218
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• 2002

The Vector Random Decrement technique has been developed as an efficient method for transforming ambient responses into free decays of linear structures. It is shown that the VRD functions nay contain as much information about the modes as the really measured free decay responses. In this paper, the theory of the VRD technique is extended by applying the concept of the mode shape ratio into the Ibrahim Time Domain modal parameter identification algorithm. The VRD function is not shifted in the correction procedures for constant time shifts of the proposed VRD technique. Thus, a number of points equal to the largest of the time shifts used in the vector triggering condition are not deleted. In the VRD functions, any influence of the input to the system is averaged out. The proposed technique is compared with the traditional VRD technique by assessment of the modal parameters. The applicability of the VRD technique has been justified through a simulation study and a study of the response of a laboratory beam model subject to ambient loads.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.63-73
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• 2021

This paper presents a algorithm for automatic target recognition robust to the influence of the flame in order to track the target by EOTS(Electro-Optical Targeting System) equipped on UAV(Unmanned Aerial Vehicle) when there is aerial target or marine target with flame at the same time. The proposed method converts infrared images of targets and flames into a gradient vector field, and applies each gradient magnitude to a polynomial curve fitting technique to extract polynomial coefficients, and learns them in a shallow neural network model to automatically recognize targets and flames. The performance of the proposed technique was confirmed by utilizing the various infrared image database of the target and flame. Using this algorithm, it can be applied to areas where collision avoidance, forest fire detection, automatic detection and recognition of targets in the air and sea during automatic flight of unmanned aircraft.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.317-324
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• 2017

An influence measure known as Cook's distance has been used for judging the influence of each observation on the least squares estimate of the parameter vector. The distance does not reflect the distributional property of the change in the least squares estimator of the regression coefficients due to case deletions: the distribution has a covariance matrix of rank one and thus it has a support set determined by a line in the multidimensional Euclidean space. As a result, the use of Cook's distance may fail to correctly provide information about influential observations, and we study some reasons for the failure. Three illustrative examples will be provided, in which the use of Cook's distance fails to give the right information about influential observations or it provides the right information about the most influential observation. We will seek some reasons for the wrong or right provision of information.

• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.57-69
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• 2000

This paper discusses the local influence approach to the linear regression models with AR(2) errors. Diagnostics for the linear regression models with AR(2) errors are proposed and developed when simultaneous perturbations of the response vector are allowed- That is, the direction of maximum curvature of local influence analysis is obtained by studying the curvature of a surface associated with the overall discrepancy measure.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.277-288
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• 2002

Influence of form errors of a chamber filled with a liquid on the movement and stability of a ball, rotating in the chamber, is studied. Two cases of the influence of the chamber form errors on the forces, acting on the ball, are defined. The first case describes the situation when limitations on the rotor shift are not imposed and disturbances of the chamber form are set by spherical harmonics not above the first order. In the second case disturbance of a chamber form is arbitrary and the rotor is supposed small. A rising here diflective moment tends to direct the angular speed vector along the small semiaxis of the ellipsoid, i.e., a stable position of the rotor appears.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.4
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• pp.451-459
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• 1998

THe influence of internal acoustic exitation through a square prism on the turbulent wake flow characteristics was investigated. The intermediate wake region where is about ten times the respective length of the body was experimentally investigated using a conditional phase average technique. At first the static base pressures of square prism and the shedding frequencies have been measured at various internal acoustic exciation frequencies. The experiment were performed under the four cases of internal acoustic excitation frequencies 0Hz 30Hz($St_e$=0.09) 65Hz($St_e$=0.20) 120Hz($St_e$=0.38) And velocity vector fields were presented and discussed. The influence of acoustic exvitation frequencies on the structure of intermediate turbulent wake region is evident. As the internal acoustic frequency increased shedding frequency gradually increased and aerodynamic force decreased. Also it was found that the vortex shedding occurs dratically well and shedding frequency reached nearly the same value as the internal acoustic frequency. but above Strouhal number 0.3 the influence disappeared.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.4
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• pp.279-285
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• 2020

An open-end winding (OEW) permanent magnet synchronous motor with dual inverters can synthesize large voltages for a motor with the same DC link voltage. This ability has the advantage of reducing the use of DC/DC boost converters or high voltage batteries. However, zero-sequence voltage (ZSV), which is caused by the difference in the combined voltage between the primary and secondary inverters, can generate a zero-sequence current (ZSC) that increases system losses. Among the methods for eliminating this phenomenon, combining voltage vector eliminated ZSV cannot be accomplished by the conventional Pulse Width Modulation(PWM) method. In this study, a PWM carrier generation method using functionalization to generate a switching pattern to suppress ZSC is proposed and applied to analyze the control influence of the center-zero vector in the switching sequence about the current ripple.