• The Journal of Engineering Geology
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• v.27 no.3
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• pp.217-231
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• 2017

The subsidence of ground in urban area can be caused by the occurrence of the cavity and the change in ground volumetric water content. The objective of this study is the detection of abnormal area of ground in urban area where the cavity or the change in ground volumetric water content is occurred by the ground penetrating radar signal. GPR survey is carried out on the test bed with a circular buried object. From the GPR survey, the signals filtered by the bandpass filtering are measured, and the methods consisting of gain function, time zero, background removal, deconvolution and display gain are applied to the filtered signals. As a result of application of the signal processing methods, the polarity of signal corresponds with the relation of electrical impedance of the cavity and the ground in test bed. In addition, the relative permittivity calculated by GPR signal is compared with that of predicted by volumetric water content of the test bed. The relative permittivities obtained from two different methods show similar values. Therefore, the abnormal area where the change in ground volumetric water content is occurred can be detected from the results of the GPR survey in case the depth of underground utilities is known. Signal processing methods and estimation of relative permittivity performed in this study may be effectively used to detect the abnormal area of ground in urban area.

• Journal of Sensor Science and Technology
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• v.5 no.2
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• pp.37-46
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• 1996

This paper describes a system that can be used to recognize unknown materials regardless of the change in ambient temperature by using temperature response curve fitting and fuzzy neural network(FNN). There are problems with a recognition system which utilize temperature responses. It requires too many memories to store the vast temperature response data and it has to be filtered to remove the noise which occurs in experiments. Thus, this paper proposes a practical method using curve fitting to remove the above problems of memories and noise. Also, the FNN is proposed to overcome the problem caused by the change of ambient temperature. Using the FNN which is learned by temperature responses on fixed ambient temperatures and known thermal conductivity, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be recognized via its thermal conductivity.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.485-490
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• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.173-191
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• 2022

In this study, the shear wave velocity of the ground was measured using Flat TDR, and the precision analysis of the measured value and the verification of field applicability were performed. The shear wave velocity measurement value was derived in the field using the piezo-stack combined in the Flat TDR. analyzed. As a result of the experiment, the average value of the change in shear wave speed at the time of grout material injection was 10.15 m/s at the beginning of age, and the average value of the change in shear wave speed after the 7th to 14th days was 65.99 m/s, showing a tendency to increase with age. Also, it was found that dry density and shear wave speed increased as the water content increased on the dry side, and that the dry density and shear wave rate decreased as the water content increased on the wet side as the water content increased. The shear modulus value derived from the field test was confirmed to be a minimum of 17.36 MPa and a maximum of 28.13 MPa, confirming a measurement value similar to the reference value. Through this, it can be seen that the measured value of the shear modulus using Flat TDR is reliable data, and it can be determined that the compaction management of the site can be effectively managed in the future.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.109-120
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• 2006

This paper addresses techniques for predicting a future path of an object moving on a road network. Most prior methods for future prediction mainly focus their attention on objects moving in Euclidean space. A variety of applications such as telematics, however, deal with objects that move only over road networks in most cases, thereby requiring an effective method of future prediction of moving objects on road networks. In this paper, we propose a novel method for predicting a future path of an object by analyzing past trajectories whose changing pattern is similar to that of a current trajectory of a query object. We devise a new function that measures a similarity between trajectories by reflecting the characteristics of road networks. By using this function, we predict a future path of a given moving object as follows: First, we search for candidate trajectories that contain subtrajectories similar to a given query trajectory by accessing past trajectories stored in moving object databases. Then, we predict a future path of a query object by analyzing the moving paths along with a current position to a destination of candidate trajectories thus retrieved. Also, we suggest a method that improves the accuracy of path prediction by regarding moving paths that have just small differences as the same group.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.157-164
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• 2023

Specifying the semantic structure for functional interfaces and lambda expressions, which are the latest features of Java, can be referenced when designing similar functions in the future, and is also required in the process of standardizing or implementing an optimized translator. In this study, action equation 3.0 is newly proposed to express the static and dynamic semantic structure of functional interfaces and lambda expressions by modifying and upgrading the existing expressions to express the semantic structures of java functional interfaces and lambda expressions. Measure the execution time of java programs by implementing the semantic structure specified in action equation 3.0 in java, and prove that action equation 3.0 is a real semantic structure that can be implemented through simulation. The superiority of this action equation 3.0 is to be confirmed by comparing the action equation 3.0 specified in the four areas of readability, modularity, extensibility and flexibility with the existing representative semantic expression methods.

• Economic and Environmental Geology
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• v.45 no.4
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• pp.377-384
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• 2012

The main field component of the Earth's magnetic field was modeled from the tri-axial magnetometer onboard KOrean MultiPurpose SATellite-II (KOMPSAT-II) for the purpose of satellite attitude control. The model computed by the KOMPSAT-II magnetometer measurement data is compared with the International Geomagnetic Reference Field (IGRF) model of a degree of up to 13 in spherical harmonic coefficients. The previous study with KOMPSAT-I (Kim et al. 2004) indicated a good correlation of power spectrum of spherical harmonic coefficients with respect to the degree up to 5. This study, however, showed an agreement of the degree up to 8-9 of the coefficient power spectrum and a discrepancy between degrees 10 and 13. We have concluded that relevant data selection process, removal of the external field from the data in the high latitude region, an accuracy of the magnetometer all play an important role in finding a coherence with the IGRF model. This study will be extended to the secular variation model of geomagnetism if longer-period data become available.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.479-486
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• 2018

In order to ensure reliable navigation performance of a lunar exploration rover, navigation algorithms using additional sensors such as inertial measurement units and cameras are essential on lunar surface in the absence of a global navigation satellite system. Unprecedentedly, Visual Odometry (VO) using a stereo camera has been successfully implemented at the US Mars rovers. In this paper, we estimate the 6-DOF pose of the lunar exploration rover from gray images of a lunar-like terrains. The proposed algorithm estimates relative pose of consecutive images by sparse image alignment based semi-direct VO. In order to overcome vulnerability to non-linearity of direct VO, we add adaptive motion prior weights calculated from a linear function of the previous pose to the optimization cost function. The proposed algorithm is verified in lunar-like terrain dataset recorded by Toronto University reflecting the characteristics of the actual lunar environment.

• Membrane Journal
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• v.13 no.1
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• pp.20-28
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• 2003

In this study, we try to formularize simultaneous equations to make a prediction about pressure drop for designing intravascular artificial lung assist device. Designing parameters to predict the effect of pressure drop and designed modules under various conditions were studied through an experimental modeling before inserting the artificial lung assist device into as venous. We measured pressure drop in various number of hollow fiber membranes, when the inside diameter of shell is fixed in 3 cm, and tried to develope the prediction equations by curve fitting based on the correlation between the experimental pressure drop and the device frontal area or packing density. The results showed that pressure drop increased with 2nd order functional formula as the liquid flow rate, the frontal area, and the packing density increased. Also, we can estimate the pressure drop as a function of the frontal area or packing density. The pressure drop obtained from the experiment was similar to that from the equation, confirming the usefulness of the equation.

• Journal of the Korea Computer Graphics Society
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• v.7 no.1
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• pp.37-49
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• 2001

We propose an optimization of mutual information for multiresolution image registration to represent useful information as integrated form obtaining from complementary information of multi modality images. The method applies mutual information as cost function to measure the statistical dependency or information redundancy between the image intensities of corresponding pixels in both images, which is assumed to be maximal if the images are geometrically aligned. As experimental results we validate visual inspection for accuracy, changning initial condition and addictive noise for robustness. Since our method uses the native image rather than prior feature extraction, few user interaction is required to perform the registration. In addition it leads to robust density estimation and convergence as applying non-parametric density estimation and stochastic multiresolution optimization.