• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.537-542
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• 2008

Cricket is an excellent indoor location system and it can successfully solve many critical problems such as user privacy, decentralized administration. But in some practical applications, Cricket sometimes didn't provide location with enough accuracy, and was unable to determine when it was giving inaccurate information. For getting high-accuracy tracking performance from location data contaminated with noise, some types of filters are required. Kalman Filter is an efficient recursive filter that estimates the state of a dynamic system from a series of incomplete and noisy measurement. The filter is very powerful in the field of autonomous and assisted navigation. In this paper, we carry out comparative studies to validate the performance of the application of Kalman Filter to Cricket based localization system.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.4
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• pp.507-520
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• 2022

The Sr isotope ratio, which is used as basic data for rock formation time, crustal and mantle evolution studies, is determined by mass spectrometer such as thermal ionization mass spectrometry (TIMS) or multi-detector inductively coupled plasma mass spectrometry (MC-ICP-MS). In this technical report, we compared how incomplete chemical separation of elements affects the determination of Sr isotope ratios. For the experiment, commercial resin, NBS987(NIST SRM987) Sr isotope standard, and rock standard samples from the Geological Survey of Japan (GSJ) such as JG1a, JB3 and JA1 were used. As a result of the comparative experiment, it was clearly observed that the measured values of ⁸⁷Sr/⁸⁶Sr change when Rb remains due to incomplete separation of the NBS987 Sr isotope standard sample as well as the rock standard samples of GSJ. This indicates that complete separation is an important factor since the calculated value deviates from the true value even though correction for isotope interference by isobar is performed when measuring the isotope ratio with MC-ICP-MS. This also suggests that, when reporting the measurement result of Sr isotope ratio using MC-ICP-MS, the measurement strength of ⁸⁵Rb should be reported together with the measurement strength of all isotopes of Sr so that isotope interference by isobar can be judged.

• Smart Structures and Systems
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• v.3 no.3
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• pp.245-261
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• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.181-188
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• 2012

In this paper, the measurement data is analyzed and channel parameters are derived through MIMO Channel measurements at 781MHz considering outdoor multi-path environment. 781MHz frequency band currently operates the DTV system. However, it will be allocated new mobile communication frequency band. The channel characteristics at 781MHz seem to be similar existing mobile communication system at 900MHz but a study on channel characteristics of signal transfer process is necessary because there is incomplete study in mobile networks at 781MHz. To avoid interference with Korean DTV broadcasting, we measured channel characteristics in city/suburban areas of Jeju island by channel sounder and $4{\times}4$ antenna of the ETRI(Korea Electronics and Telecommunications Research Institute). Path Loss, Delay Spread, Angular Spread and K-factor were derived based on measured data.

• Journal of Wetlands Research
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• v.7 no.4
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• pp.97-107
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• 2005

As the distributed model is developed and widely used, the accuracy of a rainfall measurement and more dense rainfall observation network are required for the reflection of various spatial properties. However, in reality, it is not easy to get the accurate data from dense network. Generally, we could not have the proper rainfall gages in space and even we have proper network for rainfall gages it is not easy to reflect the variations of rainfall in space and time. Often, we do also have missing rainfall data at the rainfall gage stations due to various reasons. We estimate the distribution of mean areal rainfall data from the point rainfalls. So, in the aspect of continuous rainfall property in time, we should fill the missing rainfall data then we can represent the spatial distribution of rainfall data. This study uses the Fuzzy-Genetic algorithm as a interpolation method for filling the missing rainfall data. We compare the Fuzzy-Genetic algorithm with arithmetic average method, inverse distance method, normal ratio method, and ratio of distance and elevation method which are widely used previously. As the results, the previous methods showed the accuracy of 70 to 80 % but the Fuzzy-Genetic algorithm showed that of 90 %. Especially, from the sensitivity analysis, we suggest the values of power in the equation for filling the missing data according to the distance and elevation.

• Journal of the Korean Geotechnical Society
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• v.19 no.4
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• pp.133-144
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• 2003

The resonant column testing is a laboratory testing method to determine the shear modulus and material damping factor of soils. The method has been widely used for many applications and its importance has increased. Since the first use of the testing method in 1960's, the low-technology electronic devices fir testing and data acquisition have limited the measurement only to the amplitude of the linear spectrum. The limitations of the testing method are also attributed to the assumption of linear-elastic material in the theory of the resonant column testing and also to the incomplete understanding of the dynamic behaviour of the resonant column testing device. Recently, Joh et al. proposed a theory to overcome the limitations of the resonant column testing by deriving the equation of motion and providing its solution for the resonant column testing device. This study proposed the improved data reduction and analysis method for the resonant column testing, thanks to the advanced data acquisition system and the new theoretical solution for the resonant column testing system. For the verification of the proposed data reduction and analysis method, the numerical simulation of the resonant column testing was performed by the finite element analysis. Also, a series of resonant column testing were performed fir Joomunjin sand, which verified the feasibility of the proposed method and revealed the limitations of the conventional data reduction and analysis method.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.

• Convergence Security Journal
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• v.17 no.5
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• pp.19-25
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• 2017

Public institutions invest about half of the information protection budget annually to introduce information security products and information protection services in order to prevent cyber terrorism and establish organizational security. However, research on whether introduced information security products has a positive influence on improving the information security level of the actual institution is in an incomplete state, and accordingly, There are problems such as the measurement of the investment effect of the information security product introduced in the organization and the difficulty in selecting the optimum information security product that the agency actually needs. In this paper, prior research will conduct research on the influence of the introduction of information security products on the improvement of information security level of organization through analysis of operational data of inadequate information security products, and based on the research results, It would be useful to use it for information security practices such as optimal product selection and internal security policy formulation through validation of the introduction of information security products of public institutions.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.200-206
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• 2022

This study is to develop database by an experimental method for the development of condition based maintenance for auxiliary equipment in marine engine systems. Existing ships have been performing regular maintenance, so the actual measurement data development is very incomplete. Therefore, it is best to develop a database on land tests. In this paper, a database developed by an experimental method is presented. First, failure case analysis and reliability analysis were performed to select a failure mode. For the failure simulation test, a test bed for land testing was developed. The failure simulation test was performed based on the failure simulation scenario in which the failure simulation test plan was defined. A 1.5TB failure simulation database has been developed, and it is expected to serve as a basis for ship failure diagnosis and prediction algorithm model development.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.763-774
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• 2023

The water availability in a river is related to the return flow of residential water. However it is still difficult to determine the exact return flow. In this study, the residential water-cycle system is defined as a process consisting of water inflow, water transfer and water outflow. The study area is Hampyeong-gun, Jeollanam-do, and is set as a single inflow to a single outflow through the water-cycle system after classification of complete and incomplete measurement points. The time-series prediction models(ARIMA model and TFM) are established with daily inflow and outflow data for 6 years. Inflow and outflow are predicted by dividing into training and test periods. As a result, both models show the feasibility of short-term prediction by deriving stable residuals and securing statistical significance, implementing the preliminary form of the water-cycle system. As a further study, it is suggested to predict the actual return flow of the target basin and efficient water operation by adding input factors and selecting the optimal model.