• Steel and Composite Structures
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• v.44 no.2
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• pp.155-169
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• 2022

In the present paper an analytical model was developed to study the non-linear vibrations of Functionally Graded Carbon Nanotube (FG-CNT) reinforced doubly-curved shallow shells using the Multiple Scales Method (MSM). The nonlinear partial differential equations of motion are based on the FGM shallow shell hypothesis, the non-linear geometric Von-Karman relationships, and the Galerkin method to reduce the partial differential equations associated with simply supported boundary conditions. The novelty of the present model is the simultaneous prediction of the natural frequencies and their mode shapes versus different curvatures (cylindrical, spherical, conical, and plate) and the different types of FG-CNTs. In addition to combining the vibration analysis with optimization algorithms based on the genetic algorithm, a design optimization methode was developed to maximize the natural frequencies. By considering the expression of the non-dimensional frequency as an objective optimization function, a genetic algorithm program was developed by valuing the mechanical properties, the geometric properties and the FG-CNT configuration of shallow double curvature shells. The results obtained show that the curvature, the volume fraction and the types of NTC distribution have considerable effects on the variation of the Dimensionless Fundamental Linear Frequency (DFLF). The frequency response of the shallow shells of the FG-CNTRC showed two types of nonlinear hardening and softening which are strongly influenced by the change in the fundamental vibration mode. In GA optimization, the mechanical properties and geometric properties in the transverse direction, the volume fraction, and types of distribution of CNTs have a considerable effect on the fundamental frequencies of shallow double-curvature shells. Where the difference between optimized and not optimized DFLF can reach 13.26%.

• Journal of Korean Elementary Science Education
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• v.25 no.spc5
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• pp.556-566
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• 2007

The purpose of this study was to develop an electroencephalogram (EEG) based differential-scale for scientifically gifted students in elementary school. For this study, signals of EEG with 19 channels were recorded during the generation of our scientific hypothesis using 22 scientifically gifted students, and with 49 average students being used as the control group. IQ, TCT and knowledge generation (KG) as constructs of the scientifically gifted were administered for both the scientifically gifted and the normal, control group elementary students. A 'gifted' value was added to paper test scores of the IQ, TCT, and KG constructs in order to make a personal standardization score for the gifted students. As a dependent variable, the groups were divided by means of the standardization scores thus produced and as an autonomous variable, various EEG parameters were presented through linear analysis, nonlinear analysis, and interdependency measures of the EEG. Multiple linear regression analysis was applied successfully to explain the EEG parameters and to show the characteristics of the scientifically-gifted. The discrimination analysis was administered through the results of multiple linear regression of the EEG parameters thus produced. This study represents the foundation of the development of an EEG based discriminant-scale for scientifically gifted students in elementary school, because it will be able to faithfully discriminate between scientifically-gifted and average students. The results of this study indicates that most of the EEG parameters produced can contribute to predicting the characteristics of the scientifically-gifted in that they express the degree of mutual information and the coherence of mutuality. Accordingly, mutual connectivity which appears to originate in the brain seems to the core of discrimination.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.551-568
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• 2018

Purpose: This study addressed the relationship between technological innovation activity and management efficiency of Korean automobile firms. We tested the hypothesis of non-liner relationship of innovation activity in relation to management efficiency. Methods: We discussed prior literature in the firm innovation strategy and management efficiency studies to provide better understanding of relationships between technological innovation activity and management efficiency. As a result, we developed develop and tested a model (Inverted-U shaped) capturing the non-linear impact of technological innovation activity. While we used R&D expenditure and patent registration data for measuring firms' innovation activity, management efficiency was evaluated by using DEA(Data Envelopment Analysis). Results: Main findings of our empirical analysis indicated that the relationships between technological innovation activity and management efficiency was inverted U shaped. This implied that the relationship between technological innovation and management efficiency is inverted U-shaped non-linear, with management efficiency increasing up to a point, beyond which higher levels of R&D and patent registration activities led to a decrease in management efficiency. Conclusion: This study empirically assessed the inconclusive findings of previous research in the area of effects of innovation activities in relation to firm performance. The paper also provided theoretical and practical implications for firms who explore efficient strategy to promote the management performance through technological innovation activities. Future research directions with the limitation of the study was discussed.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.105-110
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• 2018

Korea has entered to 'aged society', which the elderly people over 65 years old is over 14% of total population. This paper aims to analyze the traffic accident by aging level. In pursuing the above, this paper focuses on modeling the traffic accident severity based on three aging levels. The main results are as follows. First, the ratio of fatal and serious injured persons (FSI) is judged to increase according to increasing aging level. Second, the null hypothesis that there is no difference in FSI among three aging levels (aging, aged, and super-aged) is rejected. Four accident severity generalized linear models which are all statistically significant have been developed. Third, the common variables are analyzed to be median age, the number of hospital beds per persons, and turn signal usage ratio. Fourth, the differentiated traffic safety policies fitted to aging levels are required. The enforcement of traffic law violation and safety enhancement of motorcycle in the region of 'aging society', improvement of traffic facilities in the region of 'aged society', and expansion of transportation facilities in the region of 'super-aged society' are evaluated to be indispensable.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.181-196
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• 2020

Based on the resource-based perspective, this study seeks to understand the relationship between the organizational slack and innovation, and to demonstrate that there exists a difference in the influence of the organizational slack according to the type of innovation by dividing the types of innovation into exploratory and exploitative innovations. They also want to understand the role that network diversity plays in the relationship between organizational slack and innovation. For this purpose, hypothesis and research models were presented based on resource-based perspectives and empirical analysis was conducted on 171 companies. The analysis confirmed that the impact of organizational slack on exploitative innovation is linear, not non-linear, as expected. In other words, the more resources available, the more productive the enterprise is, and the more resources available to the organization have a positive impact on the innovation. On the other hand, exploratory innovation represented an inverse U-shaped relationship between organizational slack and nonlinearity as expected. The control effect of network diversity was only seen in the relationship between organizational slack and exploratory innovation. Through this study, it provides implications such as the importance of network diversity, which is a relationship between companies, and the difference in the utilization of organizational slack according to the type of innovation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.545-554
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• 2019

This research aims to provide a building area extraction approach over the areas where data acquisition is impossible through field surveying, aerial photography and lidar scanning. Hence, high-resolution satellite images, which have high accessibility over the earth, are utilized for the automated building extraction in this study. 3D point clouds or DSM (Digital Surface Models), derived from the stereo image matching process, provides low quality of building area extraction due to their high level of noises and holes. In this regards, this research proposes a hybrid building area extraction approach which utilizes 3D point clouds (from image matching), and color and linear information (from imagery). First of all, ground and non-ground points are separated from 3D point clouds; then, the initial building hypothesis is extracted from the non-ground points. Secondly, color based building hypothesis is produced by considering the overlapping between the initial building hypothesis and the color segmentation result. Afterwards, line detection and space partitioning results are utilized to acquire the final building areas. The proposed approach shows 98.44% of correctness, 95.05% of completeness, and 1.05m of positional accuracy. Moreover, we see the possibility that the irregular shapes of building areas can be extracted through the proposed approach.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.265-273
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• 2020

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

• Geomechanics and Engineering
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• v.31 no.5
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• pp.439-452
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• 2022

A forecast of slope behavior during catastrophic events, such as earthquakes is crucial to recognize the risk of slope failure. This paper endeavors to eliminate the significant supposition of predefined slip surfaces in the slope stability analysis, which questions the relevance of simple conventional methods under seismic conditions. To overcome such limitations, a methodology dependent on the slip line hypothesis, which permits an automatic generation of slip surfaces, is embraced to trace the extreme slope face under static and seismic conditions. The effect of earthquakes is considered using the pseudo-static approach. The current outcomes developed from a parametric study endorse a non-linear slope surface as the extreme profile, which is in accordance with the geomorphological aspect of slopes. The proposed methodology is compared with the finite element limit analysis to ensure credibility. Through the design charts obtained from the current investigation, the stability of slopes can be assessed under seismic conditions. It can be observed that the extreme slope profile demands a flat configuration to endure the condition of the limiting equilibrium at a higher level of seismicity. However, a concurrent enhancement in the shear strength of the slope medium suppresses this tendency by offering greater resistance to the seismic inertial forces induced in the medium. Unlike the traditional linear slopes, the extreme slope profiles mostly exhibit a steeper layout over a significant part of the slope height, thus ensuring a more optimized solution to the slope stability problem. Further, the susceptibility of the Longnan slope failure in the Huining-Wudu seismic belt is predicted using the current plasticity approach, which is found to be in close agreement with a case study reported in the literature. Finally, the concept of equivalent single or multi-tiered planar slopes is explored through an example problem, which exhibits the appropriateness of the proposed non-linear slope geometry under actual field conditions.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.662-667
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• 2022

Computing music similarity is an indispensable component in developing music search service. This paper focuses on learning a music similarity function in order to boost cover song identification performance. By using the probabilistic linear discriminant analysis, we construct a latent music space where the distances between cover song pairs reduces while the distances between the non-cover song pairs increases. We derive a music similarity function by testing hypothesis, whether two songs share the same latent variable or not, using the probabilistic models with the assumption that observed music features are generated from the learned latent music space. Experimental results performed on two cover music datasets show that the proposed music similarity improves the cover song identification performance.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.265-271
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• 2008

It is commonly believed that diseases of human or economic traits of livestock are caused not by single genes acting alone, but multiple genes interacting with one another. This issue is difficult due to the limitations of parametric-statistic methods of gene effects. So we introduce multifactor-dimensionality reduction(MDR) as a methods for reducing the dimensionality of multilocus information. The MDR method is nonparametric (i. e., no hypothesis about the value of a statistical parameter is made), model free (i. e., it assumes no particular inheritance model) and is directly applicable to case-control studies. Application of the MDR method revealed the best model with an interaction effect between the SNPs, SNP1 and SNP3, while only one main effect of SNP1 was statistically significant for LMA (p < 0.01) under a general linear mixed model.