• Title/Summary/Keyword: Data frame

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RDD with Follow-Up Texting: A New Attempt to Build a Probability-Based Online Panel in South Korea

  • Dong-Hoon Seol;Deok-Hyun Jang;Sarah Prusoff LoCascio
    • Asian Journal for Public Opinion Research
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    • v.11 no.3
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    • pp.257-273
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    • 2023
  • Conducting face-to-face surveys is difficult and cost prohibitive, necessitating a new attempt to build a probability-based panel in South Korea. Since 99.9% of adult Koreans own a mobile phone, mobile phone numbers provide a viable sampling frame. Random digit dialing (RDD) surveys were conducted August-December 2021. Of the 288,056 valid phone numbers dialed, 13,655 respondents between the ages of 19 and 69 completed a phone survey. These respondents were later invited by text message to join a panel; 3,202 of these (23.4% or 1.2% based on the number initially contacted) joined the panel. When compared to official government statistics like resident registration data, the census, or the Social Survey, this new probability-based panel can be said to be representative of the Korean population on the basis of age, gender, location, marital status, and household size after weighting is applied. However, even after weighting, panel members are more educated than the general population, white-collar workers and self-employed people are overrepresented, and blue-collar workers are underrepresented. As of February 2023, this panel has grown to 10,471 participants with plans to continue to invite more panel members in the same way. Based on the comparisons in this paper, we can regard this panel as a cost-effective, probability-based panel that may be used for various kinds of public opinion research, by researchers both within and outside of Korea. As we continue to refine and grow this panel, we hope it will become more widely used by researchers as well as provide a model for those building similar panels in other countries.

3D Rigid Body Tracking Algorithm Using 2D Passive Marker Image (2D 패시브마커 영상을 이용한 3차원 리지드 바디 추적 알고리즘)

  • Park, Byung-Seo;Kim, Dong-Wook;Seo, Young-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.587-588
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    • 2022
  • In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.

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Empirical seismic vulnerability probability prediction model of RC structures considering historical field observation

  • Si-Qi Li;Hong-Bo Liu;Ke Du;Jia-Cheng Han;Yi-Ru Li;Li-Hui Yin
    • Structural Engineering and Mechanics
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    • v.86 no.4
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    • pp.547-571
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    • 2023
  • To deeply probe the actual earthquake level and fragility of typical reinforced concrete (RC) structures under multiple intensity grades, considering diachronic measurement building stock samples and actual observations of representative catastrophic earth shocks in China from 1990 to 2010, RC structures were divided into traditional RC structures (TRCs) and bottom reinforced concrete frame seismic wall masonry (BFM) structures, and the empirical damage characteristics and mechanisms were analysed. A great deal of statistics and induction were developed on the historical experience investigation data of 59 typical catastrophic earthquakes in 9 provinces of China. The database and fragility matrix prediction model were established with TRCs of 4,122.5284×104 m2 and 5,844 buildings and BFMs of 5,872 buildings as empirical seismic damage samples. By employing the methods of structural damage probability and statistics, nonlinear prediction of seismic vulnerability, and numerical and applied functional analysis, the comparison matrix of actual fragility probability prediction of TRC and BFM in multiple intensity regions under the latest version of China's macrointensity standard was established. A novel nonlinear regression prediction model of seismic vulnerability was proposed, and prediction models considering the seismic damage ratio and transcendental probability parameters were constructed. The time-varying vulnerability comparative model of the sample database was developed according to the different periods of multiple earthquakes. The new calculation method of the average fragility prediction index (AFPI) matrix parameter model has been proposed to predict the seismic fragility of an areal RC structure.

A Study on the Characteristic Micro-Climate of Traditional Korean Houses using Computational Fluid Analysis (전산유체해석을 이용한 전통한옥 주변의 미기후 특성에 대한 연구)

  • Park, Min-Woo;You, Jang-Youl;Nam, Byung-Hee;You, Ki-Pyo
    • Journal of Korean Association for Spatial Structures
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    • v.22 no.4
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    • pp.15-22
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    • 2022
  • Micro-climate measurements and computational fluid analysis were conducted to use it as basic data for the preservation and management of the old house of Kim Myung-kwan, a traditional building that is National Folk Cultural Property No. 26. As a result of the actual measurement, the temperature and humidity are relatively evenly distributed indoors unlike outdoors, but the temperature and humidity vary depending on the time change and the installation location in the outdoors. It was found that the temperature increases after dawn and the temperature varies depending on the installation position around 14:00-15:00, when the temperature becomes the highest. In particular, the temperature was high at the outdoor measurement point adjacent to the building and the fence. As a result of the computational fluid analysis, the temperature was high in the buildings and fences in the old house or in the area adjacent to the building, and it was about 1℃ higher than the surrounding area. In this area, it is judged that the thickening of wood will occur more severely than in other locations, and special preservation management is required.

Optimal sensor placement for structural health monitoring based on deep reinforcement learning

  • Xianghao Meng;Haoyu Zhang;Kailiang Jia;Hui Li;Yong Huang
    • Smart Structures and Systems
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    • v.31 no.3
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    • pp.247-257
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    • 2023
  • In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

Stability Analysis of DMC's Block Geometry (DMC 카메라의 블록기하 안정성 분석)

  • Lee, Jae One;Lee, Dong Min
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.6D
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    • pp.771-779
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    • 2009
  • Digital topographical maps used for GIS DB are mainly produced by the traditional way of analogue aerial photogrammetry. Therefore, analogue photos are only available for digital mapping after preprocessing such as film developing, printing and scanning. However, digital aerial camera is able to get digital image directly without preprocessing and thus the performance and efficiency of photogrammetry are extremely increased. This study aims to investigate geometric stability of digital aerial frame camera DMC (Digital Modular Camera). In order to verify the geometric stability of digital aerial camera DMC, some different block conditions with and without cross strips, GPS/INS data and variation of GCPs are introduced in the block adjustment. The accuracy results of every block condition were compared each other by computation of residuals of exterior orientation (EO) parameters. Results of study shows that the geometric stability of the block adjustment with cross strips is increased about 30% against without cross strips. The accuracy of EO parameters of block adjustment with cross strips is also increased about 2cm for X-coordinate, 3cm for Y-coordinate, 3cm for Z-coordinate, and 6" for omega, 4" for phi and 3" for kappa.

Dynamics in Election News Making: An Exploratory Study (선거보도의 역동성에 대한 탐색적 연구)

  • Lee, Han Soo
    • Korean Journal of Legislative Studies
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    • v.27 no.3
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    • pp.155-188
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    • 2021
  • This study examines dynamics in election news making. It is important to understand when and how news media produce election news in order to grasp news making and voting behavior. The news media sometimes make election news by focusing on issues and policies. Often they frame elections as a game and focus on election strategies while covering elections. This article argues that as time goes by during the election period, the number of policy news tends to decrease while the frequency of strategic news is likely to increase. Also, TV's and newspapers show distinctive patterns of election news making. In order to examine the arguments, this study categorizes election news stories into policy and strategic news stories produced during the 2020 Korean congressional elections and constructs daily time-series data of them. The results of structural break and regression analyses partially support the arguments.

Identification of Void Diameters for Cast-Resin Transformers (몰드변압기의 보이드 결함 크기 판별)

  • Jeong, Gi-woo;Kim, Wook-sung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.570-573
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    • 2022
  • This paper presents the identification of void diameters for a cast-resin transformer using an artificial neural network (ANN) model. A PD signal was measured by the Rogowski coil sensor which has the planar and thin structures fabricated on a printed circuit board (PCB), and the PD electrode system was fabricated to simulate a PD defect by a void. In addition, void samples with different diameters were fabricated by injecting air in a cylindrical aluminum frame using a syringe during the epoxy curing process. To identify the diameter of void defects, PD characteristics such as the discharge magnitude, pulse count, and phase angle were extracted and back propagation algorithm (BPA) was designed using virtual instrument (VI) based on the Labview program. From the experimental results, the BPA algorithm proposed in this paper has over 90% accurate rate to identify the diameter of void defects and is expected to use reference data of maintenance and replacement of insulation for cast-resin transformers in the on-site PD measurement.

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Measurement of Individuals' Emotional Stress Responses to Construction Noise through Analysis of Human Brain Waves

  • Hwang, Sungjoo;Jebelli, Houtan;Lee, Sungchan;Chung, Sehwan;Lee, SangHyun
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.237-242
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    • 2020
  • Construction noise is among the most critical stressors that adversely affect the quality of life of the people residing near construction sites. Many countries strictly regulate construction noise based on sound pressure levels, as well as timeslots and type of construction equipment. However, individuals react differently to noise, and their tolerance to noise levels varies, which should be considered when regulating construction noise. Although studies have attempted to analyze individuals' stress responses to construction noise, the lack of quantitative methods to measure stress has limited our understanding of individuals' stress responses to noise. Therefore, the authors proposed a quantitative stress measurement framework with a wearable electroencephalogram (EEG) sensor to decipher human brain wave patterns caused by diverse construction stressors (e.g., worksite hazards). This present study extends this framework to investigate the feasibility of using the wearable EEG sensor to measure individuals' emotional stress responses to construction noise in a laboratory setting. EEG data were collected from three subjects exposed to different construction noises (e.g., tonal vs. impulsive noises, different sound pressure levels) recorded at real construction sites. Simultaneously, the subjects' perceived stress levels against these noises were measured. The results indicate that the wearable EEG sensor can help understand diverse individuals' stress responses to nearby construction noises. This research provides a more quantitative means for measuring the impact of the noise generated at a construction site on neighboring communities, which can help frame more reasonable construction noise regulations that consider various types of residents in urban areas.

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A Prototype of Distributed Simulation for Facility Restoration Operation Analysis through Incorporation of Immediate Damage Assessment

  • Hwang, Sungjoo;Choi, MinJi;Starbuck, Richmond;Lee, SangHyun;Park, Moonseo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.339-343
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    • 2015
  • To rapidly recover ceased functionality of a facility after a catastrophic seismic event, critical decisions on facility repair works are made within a limited period of time. However, prolonged damage assessment of facilities, due to massive damage in the surrounding region and the complicated damage judgment procedures, may impede restoration planning. To assist reliable structural damage estimation without a deep knowledge and rapid interactive analysis among facility damage and restoration operations during the approximate restoration project planning phase, we developed a prototype of distributed facility restoration simulations through the use of high-level architecture (HLA) (IEEE 1516). The simulation prototype, in which three different simulations (including a seismic data retrieval technique, a structural response simulator, and a restoration simulation module) interact with each other, enables immediate damage estimation by promptly detecting earthquake intensity and the restoration operation analysis according to estimated damage. By conducting case simulations and experiments, research outcomes provide key insights into post-disaster restoration planning, including the extent to which facility damage varies according to disaster severity, facility location, and structures. Additional insights arise regarding the extent to which different facility damage patterns impact a project's performance, especially when facility damage is hard to estimate by observation. In particular, an understanding of required type and amount of repair activities (e.g., demolition works, structural reinforcement, frame installation, or finishing works) is expected to support project managers in approximate work scheduling or resource procurement plans.

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