• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.151-175
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• 2015

Although three types of the information security measures (technical, physical and managerial ones) are all together critical to maintaining information security in the organizations and should be implemented at the same time, this study aims at providing theoretical basis of establishing and implementing effective managerial security measures. The rationale behind this research objective is that it is very important to effectively perform the managerial security measures to achieve the target performance level of the technical and the physical security measures because main agents of practicing the information security measures in the organizations are staff members even though the technical and the physical ones are well constructed and implemented. In particular, this study intends to develop and propose the theoretical model applicable to providing the way of improving organizational members' intention to use information security technologies since the very intention to use them is essential to effectively establishing and promoting managerial security measures. In order to achieve the objective of this study, the factors critical to influencing upon the intention to use information security technologies are derived through systematically reviewing related theories and previous studies, and then the research model and hypotheses are proposed by logically reasoning the casual relationship among the these factors. Also, the empirical analyses are performed by conducting the survey of the organization members of domestic large companies and analyzing the structural equation model by PLS (Partial Least Squares) method. The significant results of this study can contribute to expanding the research area of managerial information security and can be applied to suggesting the practical guidelines for effectively establishing and implementing the managerial security measures in various organizations.

• Food Science of Animal Resources
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• v.31 no.1
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• pp.115-121
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• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• Information Systems Review
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• v.16 no.2
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• pp.97-124
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• 2014

This study applies the concepts of sociotechnical theory and role theory in order to verify the effects of stress (that is, technostress) created from information and computer technology (ICT) concerning role stress and performance. We suggest diverse perspectives concerning the elements leading to technostress along with the stress-creating process of ICT among organizational members. The following four major hypotheses are proposed: (1) Technostress is positively related to role stress (e.g., conflict and overload of roles), adverse psychological outcomes, and adverse IS use related outcomes, (2) Role conflict is positively related to adverse psychological outcomes and adverse IS use related outcomes, (3) Role overload is positively related to adverse psychological outcomes and adverse IS use related outcomes, and (4) Innovation support will play as a moderator between technostress, roles tress, adverse psychological outcomes and adverse IS use related outcomes. A partial least square (PLS) with data gathered data from ICT users of organizations was used to verify the proposed hypotheses. The results supported our claims excluding the hypothesis associated to the relationship between technostress and role stress. We suggest a theoretical implication based on the verification of technostress related to the current concept of stress experienced by individuals within organizations. We also propose that a practical implication concerning the opposite effect of technostress, can be utilized as a method of reducing role stress, and suggests a diagnostic tool for assessing the degree of technostress within organizations.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.4
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• pp.181-192
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• 2003

We developed a mathematical simulation model to portray the vertical distribution of soil water from the measured weather data and the known soil hydraulic properties, and then compared simulation results with the periodically measured soil water profiles obtained on Jungdong sandy loam to verify the model, In this model, we solved potential-based Richards' equation by the implicit finite difference method superimposed on the predictor-corrector scheme. We presumed that: soil hydraulic properties are homogeneous; soil water flows isothermally; hysteresis is not considered; no vapor flows; no heat transfers into the soil profiles; and water added to soil surface is distributed along the soil profile following partial displacement principle. The input data were broadly classified into two groups: (1) daily weather data such as rainfall, maximum and minimum air temperatures, relative humidity and solar radiation and (2) soil hydraulic data to approximate unsaturated hydraulic conductivity and water retention. Each hydraulic polynomial function approximated using the Chebyshev polynomial and least square difference technique in tandem showed a fairly good fit of the given set of data. Vertical distribution of soil water as approximations to the Richards' equation subject to changing surface and phreatic boundaries was solved numerically during 53 days with a comparatively large time increment, and this pattern agreed well with field neutron scattering data, except for the surface 0.1 m slab.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.84-91
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• 2009

This paper presents an online partial 3D modeling methodology that uses a mobile augmented reality system and aerial photographs, and a tracking methodology that compares the 3D model with a video image. Instead of relying on models which are created in advance, the system generates a 3D model for a real building on the fly by combining frontal and aerial views. A user's initial pose is estimated using an aerial photograph, which is retrieved from a database according to the user's GPS coordinates, and an inertial sensor which measures pitch. We detect edges of the rooftop based on Graph cut, and find edges and a corner of the bottom by minimizing the proposed cost function. To track the user's position and orientation in real-time, feature-based tracking is carried out based on salient points on the edges and the sides of a building the user is keeping in view. We implemented camera pose estimators using both a least squares estimator and an unscented Kalman filter (UKF). We evaluated the speed and accuracy of both approaches, and we demonstrated the usefulness of our computations as important building blocks for an Anywhere Augmentation scenario.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.978-984
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• 2018

Structural equation modeling is pointing to statistical procedures that simultaneously perform path analysis and confirmatory factor analysis. Today, this statistical procedure is an essential tool for researchers in the social sciences. There are as AMOS, LISREL and PLS representative tools that can perform structural equation modeling analysis. AMOS provides a convenient graphical user interface for beginners to use. PLS has the advantage of not having a constraint on normal distribution as well as a graphical user interface. Therefore, we compared and analyzed the three most commonly used tools (applications) in social sciences. Based on structural equation modeling, confirmatory factor analysis was performed using the IBM AMOS Ver. 23, the LISREL 8.70 and the SmartPLS 2.0. The comparative results show that LISREL has the highest explanatory power of dependent variables than other analytical tools. The path coefficients and T-values presented by the analysis results showed similar results for all three analysis tools. This study suggests practical and theoretical implications based on the results.

• Information Systems Review
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• v.24 no.2
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• pp.67-88
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• 2022

This study proposed a research model that can explain the usage intentions of users and non-users by considering the performance aspects of personal mobility and external environmental factors based on the SOR (Stimulus-Organism-Response) model, A survey was conducted targeting domestic users and non-users, and research models and hypotheses were verified through Partial Least Square (PLS) and Artificial Neural Network (ANN). As a result of the analysis, it was confirmed that the users' perceived satisfaction and perceived trust had a positive effect on their intention to use, and that perceived risk and environmental value had a significant relationship with perceived satisfaction and perceived trust. For non-users, it was found that there was a positive correlation between perceived satisfaction and intention to use, and it was verified that perceived risk and environmental value, like users, were significant antecedents of perceived satisfaction and perceived trust. Among the remaining variables, the perceived mobility of users and the perceived ease of use of non-users were respectively presented as important influencing factors on perceived satisfaction.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.717-726
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• 2009

Multivariate models were developed for the simultaneous spectrophotometric determination of copper (II), nickel (II) and zinc (II) in water with 1-(2-thiazolylazo)-2-naphthol as chromogenic reagent in the presence of Triton X-100. To overcome the drawback of spectral interferences, principal component regression (PCR) and partial least square (PLS) multivariate calibration approaches were applied. Performances were validated with several test sets, and their results were then compared. In general, no significant difference in analytical performance between PLS and PCR models. The root mean square error of prediction (RMSEP) using three components for $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ were 0.018, 0.010, 0.011 ppm, respectively. Figures of merit such as sensitivity, analytical sensitivity, limit of detection (LOD) were also estimated. High reliability was achieved when the proposed procedure was applied to simultaneous determination of $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ in synthetic mixture and tap water.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

• Korean Journal of Optics and Photonics
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• v.20 no.6
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• pp.346-353
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• 2009

Glucose and protein in urine are among the important substances for urine analysis and have generally been measured based on a reagent strip test. In this study, these two substances were measured using mid-infrared absorption spectroscopy. Samples were prepared from a commercial synthetic urine product. Glucose and albumin were added as well as red blood cells, which are expected to create the most spectroscopic interference of any substance. Concentrations of these substances were varied independently. Optimal wavelength regions were determined from a partial least squares regression analysis (glucose 980 - 1150/cm, albumin 1400 - 1570/cm). Interference by other substances increased the differences between measured and predicted values. Albumin measurement in particular weres heavily influenced by the presence of glucose and red blood cells. Depending on the inference by other substances, measurement errors were 29.85${\sim}$45.19 mg/dl for a glucose level between 0 and 1000 mg/dl and 14.0${\sim}$93.11 mg/dl for an albumin level of 0 ${\sim}$ 500 mg/dl. Our study proposes an alternative to the chemical test-strip analysis, which shows only discrete concentration levels.