• Journal of Navigation and Port Research
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• v.43 no.6
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• pp.335-343
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• 2019

As the regulations of ship exhaust gas have been strengthened recently, many measures are under consideration to reduce fuel consumption. Among them, research has been performed actively to develop a machine-learning model that predicts fuel consumption by using data collected from ships. However, many studies have not considered the methodology of the main parameter selection for the model or the processing of the collected data sufficiently, and the reckless use of data may cause problems such as multicollinearity between variables. In this study, we propose a method to predict the fuel consumption of the ship by using the principal component analysis to solve these problems. The principal component analysis was performed on the operational data of the 13K TEU container ship and the fuel consumption prediction model was implemented by regression analysis with extracted components. As the R-squared value of the model for the test data was 82.99%, this model would be expected to support the decision-making of operators in the voyage planning and contribute to the monitoring of energy-efficient operation of ships during voyages.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.5-8
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• 2005

The purpose of this study is to investigate the mechanical characteristics of plain and steel fiber high strength concrete under uniaxial and biaxial loading condition. A number of plain and steel fiber high strength concrete cubes having 28 days compressive strength of 82.7Mpa (12,000psi) were made and tested. Four principal compression stress ratios, and four fiber concentrations were selected as major test variables. From test results, it is shown that confinement stress in minor stress direction has pronounced effect on the strength and deformational behavior. Both of the stiffness and ultimate strength of the plain and fiber high strength concrete increased. The maximum increase of ultimate strength occurred at biaxial stress ratio of 0.5 in the plain high strength concrete and the value were recorded 30 percent over than the strength under uniaxial condition. The failure modes of plain high strength concrete under uniaxial compression were shown as splitting type of failure but steel fiber concrete specimens under biaxial condition showed shear type failure.

• Proceedings of the Korea Concrete Institute Conference
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• 1991.10a
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• pp.107-112
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• 1991

The object of this study is to investigate material characteristics and flexural behavior of high strength concrete. Principal causes of variations of high compressive strength include the strength-producing capabilities of cement and silica hume. Compressive strength of 1200 kgf/$\textrm{cm}^2$ is introduced for identifying the effect of the variation of the size of porocity and alternative method of measurement, Acoustic Emition method, is applied to examine the phenominon of concrete failure. The main test variables in the beam element are tensile steel ratios, presence of shear reinforcement, and change of steel shape. The estimation of stress block in the flexural test of this element tends to support the present theory and may suggest a desirable shape of the stress block.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.1 s.41
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• pp.73-83
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• 1992

This paper examined risk reduction methods utilized by consumers in apparel buying situation in multidimensional conceptual framework, and analyzed the relationships between risk types, consumer demographic variables and preferences of risk reduction methods. Samples of 224 consumers were deliberately selected to include various demographic characteristics such as sex, age, educational level, occupation, income level. The results of the principal axis factor analysis indicated that 26 item risk reduction methods could be summarized into 6 meaningful factors; Marketer-dominated Information Sources Use (MIS), Prepurchase Deliberation / Observation i Dependence on Past Buying Experience (DOE), Independent Information Sources Use (lIS), Interpersonal Information Sources Use (PIS), Brand Loyalty (BL), Label Reading / Guarantee Buying (RG). DOE were used most whereas IIS used least. Correlations of various types of risk perceived with the preference of risk reduction methods were significant especially for positive relationship between psychologi-cal and/or economic risk and DOE, and between social risk and/or fashionability loss and MIS. Results of ANOVA and Duncan test suggested that sex, age, educational level, occupation of consumers can act as ones of determinant variables on making differences in the use of risk reduction methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.105-112
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• 2022

The current study is at the forefront of examining the theory of principal-agent framework and financing constraints to explain the level of corporate innovation. To boost the firm's level of innovation, this study uses corporate governance and corporate performance as driving factors. The study's secondary goal is to give information on the parallel relationship between corporate governance and the level of corporate innovation. This study used a two-step least square (TSLS) regression analysis to examine such a simultaneous association using secondary data from Indonesian listed businesses from 2000 to 2021, which totaled around 1,910 observations. This study uses the Principal Component Analysis (PCA) tool to test cumulative variances of potential corporate governance indicators such as the total commissioner of the firm (TCOM), total independent commissioner of the firm (INDPCOM), the proportion of institutional ownership (INSOWN), total female commissioner (FEMCOM), CEO duality (CEODUAL), and type of the firm (SOE). As a result, PCA reveals that four of these variables, omitting CEODUAL and SOE, were a corporate governance construct. Furthermore, the study discovered that the amount of firm innovation and corporate governance are related.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.

• Spatial Information Research
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• v.21 no.3
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• pp.71-78
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• 2013

Continuous management of bicycle facilities is needed, as uses of bicycles are increased. In the previous studies, evaluation of bicycle facilities were performed mainly from the surveys to bicycle users and experts. This study aims to evaluate the facilities for bicycle uses by setting up the quantitative assessing measures for the purpose of contributing to balanced management of the facilities for bicycle uses. Based on the existing measures provided in the previous studies about conditions for bicycles users, the variables of the facilities that are available and quantifiable were derived, and the scales of the facilities were set up. For evaluation, the station influence areas in Songpa District were selected as test areas. The methods for analysis were, first, to carry out the 'bicycle roads-facilities' analysis, which was modified from quadrant method. Consequently, individual facilities and station areas were relatively examined. Second, by principal component analysis, bicycle facilities were analyzed in a general and integrated way. From that, the variables sharing common characteristics were grouped, similar types of stations influence areas were found out, and then the groups were ranked.

• Ocean and Polar Research
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• v.26 no.2
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• pp.333-339
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• 2004

This paper is concerned with an experimental investigation about tractive performance of a tracked vehicle on extremely soft soil. A tracked vehicle model with principal dimensions of $0.9\;m(L)\;{\times}\;0.75\;m(B)\;{\times}\;0.4\;m(H)$ and the weight of 167 kg was constructed with a pair of driving chain links driven by two AC-servo motors. The tracks are configured with detachable grousers with variable span. Deep seabed was simulated by means of bentonite-water mixture in a soil bin of $6.0\;m(L)\;{\times}\;3.7\;m(B)\;{\times}\;0.7\;m(H)$. Slip of vehicle and driving torque of motor were measured with respect to experimental variables; grouser span, grouser chevron angle, driving speed, drawbar-pull weight, position of center-of-gravity and weight. $L_8$ orthogonal array is adopted for DOE (Design Of Experiment). The effects of experiment variables on traction performance are evaluated.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.40-46
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• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• Magazine of the Korea Concrete Institute
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• v.2 no.2
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• pp.93-99
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• 1990

The object of this study was to investigate the flexural stress blocks of High Strength Concrete Members under monotonic loading. Such a stress block should be clearly idealized before High Strength Concrete can be used with confidence in Structural Members. The principal test variables were the Compressive Strength of Concrete, the percentage of longitudinal reinforcement and the spacing of confinement reinforcement. The rectangular stress block of the present ACI Building Code was found to give acceptably conservative flexural strength predictions over the entire range of concrete strength from 280kg/crd (4Ksi)to 1050kg/crd( 15Ksi)