• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.17-28
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• 2021

The purpose of the research was to examine the effect of field of view on egocentric distance perception in the real and virtual environment. The replica that mimicked the real environment condition was used to create the virtual environment condition. We manipulated field of view levels equally in both viewing conditions using glasses that limit the field of view in real-world conditions and limiting the field of view in virtual-world conditions in a manner equivalent to real-world conditions via HMD. Eighteen participants observed the target with a limited field of view in a real and virtual environment without head movement. Then, we measured perceived distance using the timed imagined walking method, which measures the time taken by each participant to mentally walk to the target. The target was shown three times at three different distances from the participants: 3, 4, and 5 m. For the analysis, we converted time estimates into distance estimates. Consequently, the estimated distance in the virtual environment condition was less than the estimated distance in the real environment condition. And as the field of view shrank, the estimated distance also decreased. The estimated distance did not vary with field of view levels in real-world conditions. In the virtual environment, the estimated distance decreased as the field of view decreased, whereas in the real environment, the estimated distance increased. The implications of the results and some future research directions are discussed below.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.139-159
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• 2022

As interest in health functional foods has increased since COVID-19, the importance of imported food safety inspections is growing. However, in contrast to the annual increase in imports of health functional foods, the budget and manpower required for inspections for import and export are reaching their limit. Hence, the purpose of this study is to propose a machine learning model that efficiently detects unsuitable food suitable for the characteristics of data possessed by government offices on imported food. First, the components of food import/export inspections data that affect the judgment of nonconformity were examined and derived variables were newly created. Second, in order to select features for the machine learning, class imbalance and nonlinearity were considered when performing exploratory analysis on imported food-related data. Third, we try to compare the performance and interpretability of each model by applying various machine learning techniques. In particular, the ensemble model was the best, and it was confirmed that the derived variables and models proposed in this study can be helpful to the system used in import/export inspections.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.125-134
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• 2022

Due to the development of smartphone technology, as of 2020, 91.9% of people use the Internet[1] to frequently acquire information through websites and mobile apps. As the number of homepages in charge of providing information is increasing every year, the number of applications for web vulnerability diagnosis, which diagnoses the safety of homepages, is also increasing. In the existing web vulnerability check, the number of diagnostic personnel should increase in proportion to the number of homepages that need diagnosis because the diagnosticians manually test the homepages for vulnerabilities. In reality, however, there is a limit to securing a web vulnerability diagnosis manpower, and if the number of diagnosis manpower is increased, a lot of costs are incurred. To solve these problems, an automatic diagnosis tool is used to replace a part of the manual diagnosis. This paper explores a new method to expand the current automatic diagnosis range. In other words, automatic diagnosis possible items were derived by analyzing the impact of web vulnerability diagnosis items. Furthermore, automatic diagnosis identified possible items through comparative analysis of diagnosis results by performing manual and automatic diagnosis on the website in operation. In addition, it is possible to replace manual diagnosis for possible items, but not all vulnerability items, through the improvement of automatic diagnosis tools. This paper will explore some suggestions that can help improve plans to support and implement automatic diagnosis. Through this, it will be possible to contribute to the creation of a safe website operating environment by focusing on the parts that require precise diagnosis.

• Journal of Navigation and Port Research
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• v.47 no.1
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• pp.25-36
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• 2023

To limit greenhouse gas emissions from ships, numerous environmental regulations and standards have been taken into effect. As a result, alternative fuels such as liquefied natural gas (LNG), liquefied petroleum gas (LPG), ammonia, and biofuels have been applied to ships. Most of these alternative fuels are low flashpoint fuels in the form of liquefied gas. Their use is predicted to continue to increase. Thus, management regulations for using low flash point fuel as a ship fuel are required. However, they are currently insufficient. In the case of LNG, ISO standards have been prepared in relation to bunkering. The Society for Gas as a Marine Fuel (SGMF), a non-governmental organization (NGO), has also prepared and published a guideline on LNG bunkering. The classification society also requires safety management areas to be designated according to bunkering methods and procedures for safe bunkering. Therefore, it is necessary to establish a procedure for setting a safety management area according to the type of fuel, environmental conditions, and leakage scenarios and verify it with a numerical method. In this study, as a feasibility study for establishing these procedures, application status and standards of the industry were reviewed. Classification guidelines and existing preceding studies were analyzed and investigated. Based on results of this study, a procedure for establishing a safety management area for bunkering in domestic ports of Korea can be prepared.

• Journal of the Korean Geotechnical Society
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• v.23 no.6
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• pp.97-102
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• 2007

Though the stability analysis of soil slopes widely employs the limit equilibrium method, the study on the jointed rock slopes must consider the direction of joint and the characteristics of Joint at the same time. This study analyzes the result of the change in the factors which show the characteristics of discontinuity and the shape factor of rock slopes, and so on, in an attempt to validate the propriety as to the interpretation of jointed rock slope stability which uses the general finite element program. First, the difference depending on the flow rules was compared, and the factor effect study was conducted. The selected independent variables included the direction of joint which displays the mechanical characteristics of discontinuity, adhesive cohesion, friction angle, the inclination and height of rock slope which reveal the shape of slope and surcharge load. And the horizontal displacement was numerically interpreted at the 1/3 point below the slope, a dependent variable, to compare the relative degree of factor effects. The findings of study on factor effects led to the validation that the result of horizontal displacement for each factor satisfied various engineering characteristics, making it possible to be applied to stability interpretation of jointed rock slope. A modelling is possible, which considers the application of the result of real geotechnical surveys & laboratory studies and the non-linear characteristics when designing the rock slope. In addition, the stress change which may result from the natural disaster, such as precipitation, and the construction, can be expressed. Furthermore, as the complicated rock condition and the ground supporting effect can be considered through FEM, it is considered to be very useful in making an engineering decision on the cut-slope, reinforcement and so on.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.853-861
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• 2018

This paper proposes the application of harmonic constraints to address the problems caused by abnormal voltage increases when electric railway vehicles are running. The AC line that supplies the train with power during operation is used to provide electricity of 25kV/60 Hz, but gradually the size and frequency of harmonics involved in the line are varied with the technological evolution of the railroad vehicle electrical equipment. An increase in heat losses due to the failure of the instrument transformer (PT), the main circuit device, which is a serious problem with the recent train safety operation, or to the main displacement voltage. When high frequency components are introduced through low frequency Transformers of the main circuit device, the high intensity of the components is caused by the high intensity of the core and the current flow of the parasitic core is increased, thus generating heat. To solve this problem, the recent adjustment of the sequence has applied artificial NOTCH OFF of the power converter. However, the method of receiving and controlling the OFF signal operates by interaction between the ground and the vehicle's devices, thus it is invalid in the event of failure, and an actual accident is occurring. Therefore, the harmonic currents were required to prevent possible flow of harmonics, and conducted a study to prevent accidental occurrence of train accidents and to verify feasibility of the device through the simulations of the train's experimental analysis and the simulations of the train for safe operation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.193-200
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• 2010

Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.821-829
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• 2006

Traffic load comprise primary input to pavement design causing pavement damage. therefore it should be proceeded suitable traffic load distribution modeling for pavement design and analysis. Traffic load have been represented by equivalent single axle loads (ESALs) which convert mixed traffic stream into one value for design purposes. But there are some limit to apply ESALs to other roads because it is empirical value developed as part of the original AASHO(American Association of State Highway Officials) road test. There have been many efforts to solve these problems. Several leading country have implemented M-E(Mechanistic-Empirical) design procedures based on mechanical concept. As a result, they established traffic load quantification method using load distribution model known as Axle Load Spectra. This paper details Axle Load Spectra and presents axle load distribution model based on normal mixture distribution function using truck load data collected by WIM system installed in national highway. Axle load spectra and axle load distribution model presented in this paper could be useful for basic data when making traffic load quantification plan for pavement design, overweight vehicle permit plan and pavement maintenance cost plan.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.959-975
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• 2022

Objective: To investigate the agreement and reliability of estimating the volumes and normative percentiles (N%) of segmented brain regions among NeuroQuant (NQ), DeepBrain (DB), and FreeSurfer (FS) software programs, focusing on the comparison between NQ and DB. Materials and Methods: Three-dimensional T1-weighted images of 145 participants (48 healthy participants, 50 patients with mild cognitive impairment, and 47 patients with Alzheimer's disease) from a single medical center (SMC) dataset and 130 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset were included in this retrospective study. All images were analyzed with DB, NQ, and FS software to obtain volume estimates and N% of various segmented brain regions. We used Bland-Altman analysis, repeated measures ANOVA, reproducibility coefficient, effect size, and intraclass correlation coefficient (ICC) to evaluate inter-method agreement and reliability. Results: Among the three software programs, the Bland-Altman plot showed a substantial bias, the ICC showed a broad range of reliability (0.004-0.97), and repeated-measures ANOVA revealed significant mean volume differences in all brain regions. Similarly, the volume differences of the three software programs had large effect sizes in most regions (0.73-5.51). The effect size was largest in the pallidum in both datasets and smallest in the thalamus and cerebral white matter in the SMC and ADNI datasets, respectively. N% of NQ and DB showed an unacceptably broad Bland-Altman limit of agreement in all brain regions and a very wide range of ICC values (-0.142-0.844) in most brain regions. Conclusion: NQ and DB showed significant differences in the measured volume and N%, with limited agreement and reliability for most brain regions. Therefore, users should be aware of the lack of interchangeability between these software programs when they are applied in clinical practice.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.157-168
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• 2011

Recently, the cases of freeze-thaw distress on concrete pavement in domestic have been reported periodically. Hereupon, the necessity to establish the standard of spacing factor came to the fore. The test method for analyzing spacing factor is provided in the standard of ASTM C 457. Since researchers tend to judge study results subjectively, the results should be revised throughly. Image analysis program for determining the characteristics of air-void system on hardened concrete identify air void through the difference of a color. The pixel intensity values used in this program have a significant effect on the analysis results. This study compared the automated void count by varying pixel intensity values with the manual void count in order to determine the optimum range of pixel intensity values. Also, this study analyzed the air-void characteristics on eight kinds of concrete mixtures. In this study, it was confirmed that the variation of void counted manually was around 10% from the results of round robin test, and that the optimum range of pixel intensity values is around 80~90. And it was also confirmed that air content (as a whole) was increased generally and spacing factor was decreased by increasing air-entrainer content. But some concrete mixtures showed a tendency that air content was constant and spacing factor was decreased by increasing air-entrainer content. This causes the air entrained by air-entrainer has more influence on spacing factor than air content. Also, the deviation of spacing factor by cutting position of concrete specimen was about 30~100${\mu}m$ because of the limit of 2-D image analysis. The additional study about variation of spacing factor by cutting position of concrete specimen will be performed later.