• Proceedings of the KSRS Conference
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• v.2
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• pp.892-895
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• 2006

The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water and water vapor and surface wind on surface emissivity on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor’s field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric and surface effects tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. In particular, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations over marginal ice zones.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1417-1422
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• 2005

Among the sensors mainly used for displacement measurement, there are a linear CCD(Charge Coupled Device) and a PSD(Position Sensitive Detector) as a non-contact type. Their structures are different very much, which means that the signal processing of both sensors should be applied in the different ways. Most of the displacement measurement systems to get the 3-D shape profile of an object using a linear CCD are a computer-based system. It means that all of algorithms and mathematical operations are performed through a computer program to measure the displacement. However, in this paper, the developed system has microprocessor and other digital components that make the system measure the displacement of an object without a computer. The thing different from the previous system is that AVR microprocessor and FPGA(Field Programmable Gate Array) technology, and a comparator is used to play the role of an A/D(Analog to Digital) converter. Furthermore, an ATC(Automatic Threshold Control) algorithm is applied to find the highest pixel data that has the real displacement information. According to the size of the light circle incident on the surface of the CCD, the threshold value to remove the noise and useless data is changed by the operation of AVR microprocessor. The total system consists of FPGA, AVR microprocessor, and the comparator. The developed system has the improvement and shows the better performance than the system not using the ATC algorithm for displacement measurement.

• Survey Research
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• v.11 no.3
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• pp.1-18
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• 2010

How much do people living in different communities vary in their survey responses? A few studies have examined the effect of the social environment on survey response. Making generalizations from these studies by looking at the effect of social environment on survey response is complicated due to differences in survey dimensions, including incentives, survey mode, types of response rates, and geographic levels. Using the 2000 Census Final Response Rates(CFRR) and the 2002 General Social Survey Response Rates(GSSRR) linked with the 2000 Census in the United States, we attempt to understand how community characteristics associated with survey cooperation vary between data sets. We found that people living in poor area are less likely to cooperate with the Census but more likely to cooperate with GSS, while people living in an area with more minors under 18 is more likely to cooperate with both Census and the GSS. By using two data sources with contrasting survey dimensions within the United States, our findings have implications for survey field operations and hopefully will invigorate studies about response rates in a Korean context.

• Smart Structures and Systems
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• v.20 no.2
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• pp.247-261
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• 2017

In the field of dynamic measurement and structural damage identification, it is generally known that modal frequencies may be measured with higher accuracy than mode shapes. However, the number of natural frequencies within a measurable range is limited. Accessing additional forms of modal frequencies is thus desirable. The present study is concerned about the extraction of artificial boundary condition (ABC) frequencies from modal testing. The ABC frequencies correspond to the natural frequencies of the structure with a perturbed boundary condition, but they can be extracted from processing the frequency response functions (FRF) measured in a specific configuration from the structure in its existing state without the need of actually altering the physical support condition. This paper presents a comprehensive experimental investigation into the measurability of the ABC frequencies from physical experiments. It covers the testing procedure through modal testing, the data processing and data analysis requirements, and the FRF matrix operations leading to the extraction of the ABC frequencies. Specific sources of measurement errors and their effects on the accuracy of the extracted ABC frequencies are scrutinised. The extracted ABC frequencies are subsequently applied in the damage identification in beams by means of finite element model updating. Results demonstrate that it is possible to extract the first few ABC frequencies from the modal testing for a variety of artificial boundary conditions incorporating one or two virtual pin supports, and the inclusion of ABC frequencies enables the identification of structural damages without the need to involve the mode shape information.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.393-402
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• 2011

Asbestos is a toxic material that can lead to lung cancer and other diseases. There is no information regarding areas in Korea that contain asbestos in nature; consequently we need to manage such areas with care. The purpose of this study was to construct a local graded map of asbestos exposure risk based on the natural occurrence of asbestos in rocks. We first developed a means of evaluating the asbestos exposure risk and produced thematic maps based on a field survey. In addition, we constructed a knowledge base for asbestos through analysis, representation and processes about asbestos data and prepare for the development of an evaluation model for asbestos exposure risk. The spatial analysis of asbestos exposure risk is based on a weighted-overlay analysis using expert opinion and the literature, and a fuzzy-overlay analysis using the uncertainty in the data. The map of asbestos exposure risk, compiled according to the weighted and fuzzy operations, is expected to be used to ensure safety and to reduce the risk of exposure to asbestos.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.125-134
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• 2009

Recently, as IT technology and the ubiquitous environment have diffused, the application of these techniques are being attempted in the field of traffic operations and management. Therefore, it is necessary to develop data collection systems and signal control strategies that are suitable in the ubiquitous environment and that will improve efficiency and safety of signalized intersections. The authors conducted a study on the Wireless Sensor Network (WSN) signal control strategy using a wireless communication network between individual vehicles and a signal-control system and full actuated signal control technique to propose a new signal control strategy in the ubiquitous environment. The WSN was defined to evaluate the algorithm used with PARAMICS API simulation. The simulation produced results that the WSN signal control is more effective than other signal control methods. The WSN signal control could reduce vehicle delay time to a maximum of 64% in comparison with other signal control methods in low and near saturation flow conditions.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.39-46
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• 2021

In this paper, we propose a method for the motion recognition method required in the industrial field in mixed reality. In industrial sites, movements (grasping, lifting, and carrying) are required throughout the upper full-body, from trunk movements to arm movements. In this paper, we use a method composed of sensors and wearable devices that are not vision-based such as Kinect without using heavy motion capture equipment. We used two IMU sensors for the trunk and shoulder movement, and used Myo arm band for the arm movements. Real-time data coming from a total of 4 are fused to enable motion recognition for the entire upper body area. As an experimental method, a sensor was attached to the actual clothes, and objects were manipulated through synchronization. As a result, the method using the synchronization method has no errors in large and small operations. Finally, through the performance evaluation, the average result was 50 frames for single-handed operation on the HoloLens and 60 frames for both-handed operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.10-24
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• 2014

Bicycle is a useful transportation mode that is healthy, emission-free, and environmentally compatible. Although large efforts have been made to promote the use of bicycling to date, there still exist various hurdles and limitations. One of the key issues to increase bicycling is how to gather bicycle-related data from the field and to generate valuable information for both users and operations agencies. This study proposes a method to process bicycle trajectory data which is obtained from tracing global positioning systems(GPS) equipped bicycle, which is defined as the probe bicycle. The proposed method is based on the concept of statistical quality control of data. In addition, a data collection and processing scenario in support of public bicycle system is presented. The outcomes of this study would be valuable fundamentals for developing bicycle traffic information systems that is a part of future intelligent transportation systems(ITS).

• Journal of the Korea Society for Simulation
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• v.33 no.3
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• pp.13-26
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• 2024

The CBRN(Chemical, Biological, Radiological, and Nuclear) hazard prediction model is a system that supports commanders in making better decisions by creating contamination distribution and damage prediction areas based on the weapons used, terrain, and weather information in the events of biochemical and radiological accidents. NBC_RAMS(Nuclear, Biological and Chemical Reporting And Modeling S/W System) developed by ADD (Agency for Defense Development) is used not only supporting for decision making plan for various military operations and exercises but also for post analyzing CBRN related events. With the NBC_RAMS's core engine, we introduced a CBR hazard assessment scenario analysis system that can generate contaminant distribution prediction results reflecting various CBR scenarios, and described how to apply it in specific purposes in terms of input information, meteorological data, land data with land coverage and DEM, and building data with pologon form. As a practical use case, a technology development case is addressed that tracks the origin location of contaminant source with artificial intelligence and a technology that selects the optimal location of a CBR detection sensor with score data by analyzing large amounts of data generated using the CBRN scenario analysis system. Through this system, it is possible to generate AI-specialized CBRN related to training and analysis data and support planning of operation and exercise by predicting battle field.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1275-1288
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• 2015

A microscale weather analysis module (about 1km or less) is a microscale numerical weather prediction model designed for operational forecasting and atmospheric research needs such as radiant energy, thermal energy, and humidity. The accuracy of the module is directly related to the usefulness and quality of real-time microscale weather information service in the metropolitan area. This paper suggests an object based verification method useful for spatio-temporal evaluation of the accuracy of the microscale weather analysis module. The method is a graphical method comprised of three steps that constructs a lattice field of evaluation statistics, merges and identifies objects, and evaluates the accuracy of the module. We develop lattice fields using various evaluation spatio-temporal statistics as well as an efficient object identification algorithm that conducts convolution, masking, and merging operations to the lattice fields. A real data application demonstrates the utility of the verification method.