• Journal of KSNVE
• /
• v.8 no.5
• /
• pp.821-831
• /
• 1998

The actual ground vibrations due to NATM and foundation blasting at Seoul(weathered rock), Pusan(weathered rock) and Youngkwang(quartz andesite) have been measured, and the data were analyzed using reliability index($\beta$) to determinate the vibration equations and the maximum charge weight for efficient blast. These were suggested with the division of ultimate limit state($\beta$=0), serviceability limit state($\beta$=1.28) and safety state($\beta$=3), respectively. The reliability index 0 mean 50% data line obtained by the least squares best-fit line. The reliability index 1.28 and 3 represent bounds below 90% and 99.9% of the data, respectively. In this study, reliability index $\beta$=1.28 with security and economy was suggested. The maximum charge weight equations for efficient blast were obtained in W=(Vc/384.90)1.5151.D3(Seoul), W=(Vc/579.82)1.4706.D3(Pusan). W=(Vc/1654.01)1.3456.D3(Youngkwang), and the blast vibration equatiions in V=385(SD)-1.98(Seoul), V=580(SD)-2.04(Pusan), V=1654(SD)-2.23(Youngkwang), respectively. From this study, inference and analysis methods of vibration equations using reliability theory were established.

• Investigative Magnetic Resonance Imaging
• /
• v.22 no.3
• /
• pp.141-149
• /
• 2018

Purpose: The purpose of this study is to develop a simple method to measure magnetic susceptibility of arbitrarily shaped materials through MR imaging and numerical modeling. Materials and Methods: Our 3D printed phantom consists of a lower compartment filled with a gel (gel part) and an upper compartment for placing a susceptibility object (object part). The $B_0$ maps of the gel with and without the object were reconstructed from phase images obtained in a 3T MRI scanner. Then, their difference was compared with a numerically modeled $B_0$ map based on the geometry of the object, obtained by a separate MRI scan of the object possibly immersed in an MR-visible liquid. The susceptibility of the object was determined by a least-squares fit. Results: A total of 18 solid and liquid samples were tested, with measured susceptibility values in the range of -12.6 to 28.28 ppm. To confirm accuracy of the method, independently obtained reference values were compared with measured susceptibility when possible. The comparison revealed that our method can determine susceptibility within approximately 5%, likely limited by the object shape modeling error. Conclusion: The proposed gel-phantom-based susceptibility measurement may be used to effectively measure magnetic susceptibility of MR-compatible samples with an arbitrary shape, and can enable development of various MR engineering parts as well as test biological tissue specimens.

• Journal of Information Processing Systems
• /
• v.10 no.3
• /
• pp.395-411
• /
• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• Journal of the Korean Chemical Society
• /
• v.45 no.3
• /
• pp.201-207
• /
• 2001

The dielectric relaxation study for aniline-dimethylsulphoxide (DMSO) and aniline-dim.ethylformamide(DMF) has been carried out using the Time domain reflectometry (TDR) technique, at different temperature and concentrations, in the frequency range of 10 MHz to 10 GHz. The dielectric parameters viz. static permittivity, relaxation time, the Kirkwood correlation factor, excess permittivity, excess inverse relaxation time and thermodynamic parameters have been obtained. The calibration method based on least squares fit method has been used. The dielectric parameters show systematic change with temperature and concentrations.

• Journal of Positioning, Navigation, and Timing
• /
• v.5 no.1
• /
• pp.1-9
• /
• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• Structural Engineering and Mechanics
• /
• v.76 no.5
• /
• pp.653-661
• /
• 2020

The paper presents a study regarding rubber compressibility behavior. The objective is to analyze the effect of compression degree of rubber on its mechanical properties and propose a new methodology based on reverse engineering to predict compressibility degree based on uniaxial stretching test and Finite Element Analysis (FEA). In general, rubbers are considered to be almost incompressible and Poisson's ratio is close to 0.5. Since this property is intimately related to the rubber packing density, little changes in Poisson's ratio can lead to significant changes regarding mechanical behavior. The deviatory hyperelastic constants were obtained through experimental data fitting by least squares method for the most relevant constitutive models implemented in commercial software Abaqus, such as: Neo-Hooke, Mooney-Rivlin, Ogden, Yeoh and Arruda-Boyce, whereas the hydrostatic part was determined through an optimization algorithm implemented in the Abaqus environment by Python scripting. The simulation results presented great influence of the Poisson's ratio in the rubber specimen mechanical behavior mainly for high strain levels. A conventional pure volumetric compression test was also carried out in order to compare the results obtained by the proposed methodology.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.307-315
• /
• 2021

The study aims to investigate the relationship between innovation activities and business process performance in higher education institution (hereinafter referred to as "HEI") context. The data was collected using a survey and later analyzed through Partial Least Squares Structural Equation Modelling (PLSSEM) and SmartPLS software. A total of 50 questionnaires were submitted from respondents representing vocational study program management located in Makassar, Indonesia. The findings show that two hypotheses discussed in this study fit the empirical data. Specifically, the results show that there is a positive relationship between innovation activities and business process performance, involving two types of innovation activities, which are exploration activities and exploitation activities, within HEIs. Explorative activity is firmly related to exploitative activity, which furthermore links to business process performance within the HEIs observed. The results confirm that exploration activity can stimulate and lead the HEIs management to generate exploitation activity. For instance, capabilities to absorb knowledge from the external institution may lead this institution to generate advanced academic processes, as well as more efficient and effective managerial processes. The study also signifies ambidexterity capacity, suggesting that it may lead HEIs management to formulate proper strategies in achieving better performance and gaining competitive advantage.

• Journal of Information Science Theory and Practice
• /
• v.10 no.3
• /
• pp.24-39
• /
• 2022

Online learning is becoming ubiquitous worldwide because of its accessibility anytime and from anywhere. However, it cannot be successfully implemented without understanding constructs that may affect its adoption. Unlike previous literature, this research extends the Unified Theory of Acceptance and Use of Technology with three well-known theories, namely compatibility, online self-efficacy, and knowledge sharing and acquisition to examine online learning adoption. A total of 264 higher education students took part in this research. Partial Least Squares-Structural Equation Modeling was used to evaluate the proposed theoretical model. The findings suggested that performance expectancy and compatibility were significant predictors of behavioral intention, whereas behavioral intention, facilitating conditions, and compatibility had a significant and direct effect on online learning's actual use. The results also showed that knowledge acquisition, knowledge sharing, and online self-efficacy were determinates of performance expectancy. Finally, online self-efficacy was a predictor of effort expectancy. The proposed model achieved a high fit and explained 47.7%, 75.1%, 76.1%, and 71.8% of the variance of effort expectancy, performance expectancy, behavioral intention, and online learning actual use, respectively. This study has many theoretical and practical implications that have been discussed for further research.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.23-30
• /
• 2019

The purpose of this study is to find out the structure of the substance that affects antidiabetic using the candidate drug information for diabetes treatment. A quantitative structure activity relationship model based on machine learning method was constructed and major molecular descriptors were determined for each experimental data variables from coefficient values using a partial least squares algorithm. The results of the analysis of the molecular access system fingerprint data reflecting the candidate drug structure information were higher than those of the in vitro data analysis in terms of goodness-of-fit, and the major molecular expression factors affecting the antidiabetic effect were also variously derived. If the proposed method is applied to the new drug development environment, it is possible to reduce the cost for conducting candidate screening experiment and to shorten the search time for new drug development.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.1
• /
• pp.43-51
• /
• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.