• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.2
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• pp.210-222
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• 2021

Purpose: This study was conducted to develop and test the effects of a nursing information literacy competency education program for undergraduate nursing students. Methods: A non-equivalent control group pretest-posttest design was used. The subjects consisted of 42 sophomore undergraduate nursing students who had completed a fundamental nursing course (experimental group: n=21, control group n=21). The nursing information literacy competency education program consisted of 8 steps in 8 sessions, taught over 4 weeks, which was 20 hours in total. Data were collected between January 23 and March 14, 2019 and were analyzed using Chi-square test, Fisher's exact test, t-test, paired t-test, and repeated measure ANOVA with SPSS/WIN 23.0. Results: Significant differences were shown between the experimental and control groups regarding nursing information literacy competency (F=91.74, p<.001), problem-solving ability (F=52.43, p<.001), self-directed learning ability (F=36.61, p<.001), and evidence-based practice competency (F=59.66, p<.001). Conclusion: The nursing information literacy competency education program was effective in improving the nursing information literacy competency, problem-solving ability, self-directed learning ability, and evidence-based practice competency of nursing students. Hence, we recommend the nursing information literacy education program will be included as an independent course in the nursing curriculum for undergraduate nursing students to promote a needed proficiency in nursing information literacy competency.

• Journal of Korean Critical Care Nursing
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• v.5 no.1
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• pp.1-11
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• 2012

Purpose:The purpose of this study was to examine the effects of video-centered information among family members intensive care unit (ICU). Methods: A quasi-experimental, nonequivalent control group, pretest-posttest design was used. Participants (n=86) were family members who were the main caregivers for the patient in ICU. An experimental group (n=43) watched a video while the control group (n=43) was provided a leaflet. Levels of environmental stress, anxiety and nursing need satisfaction were measured by questionnaires before and after the interventions. Data were analyzed with ${\chi}^2$ test, paired t-test, independent t-test, Fisher's exact test and ANCOVA. Results: There were no differences in environmental stress (F=1.88, $p$=.065), and anxiety (t=0.37, $p$=.711) between 2 groups, but there was a significant difference in nursing need satisfaction (t=3.01, $p$=.004). Conclusion: Providing video-centered information would be an effective nursing intervention by improving nursing need satisfaction among family, the main caregivers members of patients in ICU.

• The Journal of Information Technology
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• v.3 no.1
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• pp.177-189
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• 2000

It was investigated this study how much individual's job stress would be explained by formalized task environment. also, would be explained locus of control as moderate variable. The data used in the study were collected from employees in domestic corporate. After sending the total of 150 questionnaires, 113 responses were returned. Among the returned questionnaires, 9 poor responses were excluded, and the remained 104 copies were analyzed. The final regression model included formalized task environment as statistically significant, but locus of control as statistically non-significant. it was relied on a lack of sample. This study was to open job stress studies up multi level study(individual - organizational level).

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.203-210
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• 2002

For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.94-98
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• 2009

In this paper, we deal with a face recognition method for the emotional face images. Since the face recognition is one of the most natural and straightforward biometric methods, there have been various research works. However, most of them are focused on the expressionless face images and have had a very difficult problem if we consider the facial expression. In real situations, however, it is required to consider the emotional face images. Here, three basic human emotions such as happiness, sadness, and anger are investigated for the face recognition. And, this situation requires a robust face recognition algorithm then we use a fuzzy Fisher's Linear Discriminant (FLD) algorithm with the wavelet transform. The fuzzy Fisherface is a statistical method that maximizes the ratio of between-scatter matrix and within-scatter matrix and also handles the fuzzy class information. The experimental results obtained for the CBNU face databases reveal that the approach presented in this paper yields better recognition performance in comparison with the results obtained by other recognition methods.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.468-488
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• 2016

The paper proposes a novel framework for 3D face verification using dimensionality reduction based on highly distinctive local features in the presence of illumination and expression variations. The histograms of efficient local descriptors are used to represent distinctively the facial images. For this purpose, different local descriptors are evaluated, Local Binary Patterns (LBP), Three-Patch Local Binary Patterns (TPLBP), Four-Patch Local Binary Patterns (FPLBP), Binarized Statistical Image Features (BSIF) and Local Phase Quantization (LPQ). Furthermore, experiments on the combinations of the four local descriptors at feature level using simply histograms concatenation are provided. The performance of the proposed approach is evaluated with different dimensionality reduction algorithms: Principal Component Analysis (PCA), Orthogonal Locality Preserving Projection (OLPP) and the combined PCA+EFM (Enhanced Fisher linear discriminate Model). Finally, multi-class Support Vector Machine (SVM) is used as a classifier to carry out the verification between imposters and customers. The proposed method has been tested on CASIA-3D face database and the experimental results show that our method achieves a high verification performance.

• Journal of Navigation and Port Research
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• v.35 no.2
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• pp.149-157
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• 2011

The objective of this study was to compare the attitude of merchant marine student of Thailand in 3 aspects; cognitive, affective and behavioral classified by institutes, domiciles, parent's occupation, parent's income per month, motivation and information receiving concerning mariner profession. The sample used in this study consisted of 867students in maritime institutes of Thailand. The instrument implemented in collecting data was a set of 30 five rating scale questionnaires. The statistical methods applied in analyzing the data were mean, standard deviation, t-test and one way analysis of variance and fisher's LSD. The results of this research shows that the attitude in vocational education of Thai merchant marine student was of the high in every aspect. Attitude for mariner profession of Thai merchant marine student in terms of different institutes had different in all aspects. In terms of different domiciles, it shows different attitude in affection and similar attitude in cognition and behavior. In terms of parent's occupation, it shows similar in all aspects. In terms of parent's income per month, it shows different attitude in cognition and affection and similar attitude in behavior. In terms of motivation, it shows similar in all aspects. In terms of information receiving concerning mariner profession, it shows different attitude in all aspects.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.111-120
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• 2017

In this paper, we propose novel feature extraction algorithm for classification of seabed sediment. In previous researches, acoustic reflection coefficient has been used to classify seabed sediments, which is constant in terms of frequency. However, attenuation of seabed sediment is a function of frequency and is highly influenced by sediment types in general. Hence, we developed a feature vector by using attenuation variation with respect to frequency. The attenuation variation is obtained by using reflected signal from the second sediment layer, which is generated by broadband chirp. The proposed feature vector has advantage in number of dimensions to classify the seabed sediment over the classical scalar feature (reflection coefficient). To compare the proposed feature with the classical scalar feature, dimension of proposed feature vector is reduced by using linear discriminant analysis (LDA). Synthesised acoustic amplitudes reflected by seabed sediments are generated by using Biot model and the performance of proposed feature is evaluated by using Fisher scoring and classification accuracy computed by maximum likelihood decision (MLD). As a result, the proposed feature shows higher discrimination performance and more robustness against measurement errors than that of classical feature.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.197-206
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• 2014

Motor imagery based Brain-computer Interface(BCI), which has recently attracted attention, is the technique for decoding the user's voluntary motor intention using Electroencephalography(EEG). For classifying the motor imagery, event-related desynchronization(ERD), which is the phenomenon of EEG voltage drop at sensorimotor area in ${\mu}$-band(8-13Hz), has been generally used but this method are not free from the performance degradation of the BCI system because EEG has low spatial resolution and shows different ERD-appearing band according to users. Common spatial pattern(CSP) was proposed to solve the low spatial resolution problem but it has a disadvantage of being very sensitive to frequency-band selection. Discriminative filter bank common spatial pattern(DFBCSP) tried to solve the frequency-band selection problem by using the Fisher ratio of the averaged EEG signal power and establishing discriminative filter bank(DFB) which only includes the feature frequency-band. However, we found that DFB might not include the proper filters showing the spatial pattern of ERD. To solve this problem, we apply a band-selection process using CSP feature vectors and linear discriminant analysis to DFBCSP instead of the averaged EEG signal power. The filter selection results and the classification accuracies of the existing and the proposed methods show that the CSP feature is more effective than signal power feature.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.103-118
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• 2018

This study compared the production inducement effects of primary industries between Korea, China, and Japan for the period from 2000 to 2014, by examining the forward and backward linkage effects using the World Input-Output Tables. Although research on the industrial effect of primary industries has been conducted actively, this study is contributive since it compares the differences in industrial linkage effects between Korea, China, and Japan. According to Fisher(1939)'s and Clark(1957)'s classifications of primary industries, this study classified agriculture, forestry, fishing, and mining industries as primary industries. The analysis methodology of this study is to use the World Input-Output Tables to create the industry linkage model between Korea, China, and Japan, and then conduct a comparative analysis. According to the results of this study, the forward and backward linkage effects of agriculture industry between Korea, China, and Japan are significantly different, while the forward and backward linkage effects of forestry and fishing industries between Korea, China, and Japan are partially different. By comparing the changes in industrial dependencies of primary industries due to the 4th Industrial revolution between the three countries, this study suggested the future development direction of primary industries.