• Journal of Distribution Science
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• v.7 no.3
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• pp.49-69
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• 2009

With the proliferation of electronic commerce, online transactions have become a norm. Its enormous potential, however, can be truly realized if consumers feel comfortable facing invisible sellers over the Internet, a virtual business channel. Trust has been identified as a key component in many e-Commerce studies. The purpose of this study is to find out which factors play a major role in building buyer trust and how the build-up trust affects buyer's purchase intention in online used car transactions. Based on the information asymmetry, TAM (Technology Acceptance Model), and the trust theory, our research model includes factors such as a buyer's propensity-to-trust, institutional characteristics (inspection and warranty policy), word-of-mouth referral, perceived size, and perceived benefits as independent variables. The model also includes trust as a mediate variable, purchase intention as a dependent variable, and perceived quality risk as a moderate variable. The research model is tested by analyzing 448 sample data gathered from used car websites. The result shows that the trust has significant effects on the online purchase intention, and institutional characteristics have been identified as one of the most significant factors for trust building in used car websites. For those who perceive quality risk high, actual purchasing behavior occurs only when they have trust on the used car websites, indicating that trust plays a vital role as a mediate variable. This study suggests that buyer trust on the used car websites is important to increase buyer's online purchase behavior.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.395-405
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• 2017

This study was designed to examine the degree of empathic ability, gratitude disposition, and job satisfaction, and identify that the impact on job satisfaction of psychiatric nurses. Participants were 196 psychiatric nurses from 8 psychiatric hospitals in Korea. Data were collected from October 8 to 20, 2016 and were analyzed using independent t-test, one-way ANOVA, Pearson correlation coefficients and hierarchical multiple regression with the SPSS WIN 22.0 program. The mean score of job satisfaction was $3.3{\pm}0.34$, empathic ability was $3.5{\pm}0.28$, and gratitude disposition was $4.0{\pm}0.59$. The psychiatric nurses' empathic ability and gratitude disposition affected their job satisfaction, accounting for 18.5% of the total variance. Empathic ability influenced job satisfaction significantly (B=0.52, p<.001) for 17.0% of the variance. This study suggested that the development of training programs for improving job satisfaction needs to consider their empathic ability and gratitude disposition of psychiatric nurses.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

• Education of Primary School Mathematics
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• v.19 no.3
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• pp.211-222
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• 2016

This article examines K-8 pre-service teachers' (PSTs) engagement in lesson plan modification using the eight Mathematics Teaching Practices (MTPs) in Principles to Actions, the most recent landmark publication of framework by National Council of Teachers of Mathematics (NCTM) in the U.S. The activity consisted of four phases that involved the analysis and modification of an existing lesson plan. Fifty-seven PSTs participated in the activity throughout the semester, and data from each phase was analyzed using the inductive content analysis approach. PSTs' initial conceptions of lesson planning reflected little on teaching practices (i.e., the MTPs) with more emphasis placed on the form - rather than function - of lesson elements. With the opportunity to interpret MTPs and analyze lesson plans using MTPs as an analytical lens, PSTs demonstrated various interpretations of MTPs, made efforts to incorporate MTPs into lessons, and attended to the interwoven nature of MTPs. This article also shares the challenges, conflicts, and tensions reported by PSTs during their participation of lesson plan modification; as such, the results from this study will inform the research examining the pedagogical (im)possibilities for utilizing MTPs in mathematics teacher training programs.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.9-13
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• 2013

This study which improve pretreatment method was to increase effective diagnosis of barium enema to remind a more accurate action by training precautions, method of taking medicine, time and taking suitable laxative to patient. First, A total of 504 patients who received barium enema in the E university hospital were evaluated about repretreatment proportion of patients. 176 patients who were changed with precaution were evaluated about repretreatment. Second, Both 130 patients who were not changed with the type and amount of laxative and 137 patients who were changed with it were evaluated. Repretreatment rate was reduced about 10% since changed precautions. Stomachache was reduced about 21% due to chage methode to take the laxative improved. Patients who think cleanliness degree of bowel increased that it is going very well about 11.9% since improvement and decreased that it's not bad about 16.3%. The methods which accurately recognize precautions to patient decrease repretreatment rate, inconvenience and pain of patients due to repretreatment. Expectation mentlity for accurate inspection also had increased in that patients think that cleanliness degree of bowel was increased.

• Journal of Korean Home Economics Education Association
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• v.23 no.4
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• pp.49-65
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• 2011

The survey method was used in this descriptive study. The purpose in this study was to investigate middle school home economics(HE) teachers' stages of concern, levels of use, and perception about career education, based on the Concerns Based Adoption Model(CBAM). Questionnaire was administrated to middle school HE teachers over the whole country except Jeju Island through mail or e-mail by systematic random sampling. 118 data collected from the responses were finally analyzed statistically with mean, standard deviation, frequencies, percentage, and independent-sample t-test by using SPSS/WIN 12.0 program. The results of the study were as follows: First, most-HE teachers were in stages of the personal concern (86.56) and the informational concern(85.42) about HE career education. Second, the highest number of teachers was in level of refinement(33.1%) use. Third, teachers recognized important goal of HE career education as 'understanding of diverse careers and formating of positive values and attitude about work'. Also they had generally conducted HE career education through 'Understanding Teenager' chapter of a first-year middle school. However they had struggled with difficulty such as lack of data, time, and expertise in conducting HE career education. Therefore, it is necessary that support such as development, supplies, and training opportunities of career education should be provided.

• Communications of Mathematical Education
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• v.29 no.3
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• pp.373-389
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• 2015

This study was to investigate the practice of the teachers who changed their teaching subject to Mathematics from other subjects. Teacher, A who had traditional belief and Teacher, B, non-traditional belief were chosen for the study through the questionnaire in Sep. 2014. The result indicated that Teacher, A in traditional belief showed teacher-centered teaching but Teacher, B in nontraditional belief showed inconsistent way of teaching in comparison to the original perspective. The later said she could not teach students as she wanted to teach because of the lack of knowledge of teaching as a math teacher. The difficulties Teacher, A encountered were: to handle too many works beyond teaching and to teach too many contents to cover without having enough time to prepare. Teacher, B didn't know how to teach students math in a constructivism way. They asked to offer them more in-service training program to develop their expertise for teaching mathematics.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.40 no.2
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• pp.138-143
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• 2004

This experimental paper deals with the performance of tanks that are turned the active A.R.T(Anti-Rolling Tank) when the fluid transfers from wing tank to the opposite tank by the power developed by the automatic control system (INTERING Stabilizer), which was installed in the fishery training ship T/S. A - RA (G/T:990 tons) of Cheju National University. In this paper, the author has tested the performance of INTERING Stabilizer for the signals obtained by the inclinometer in irregular waves and compared with the results obtained in passive mode operation at stop and at various ship speeds. The performances of the system were confirmed the results as follows through the tests: 1. The average amplitude and significant roll (${\pi}$1/3) of the passive and active mode operations in the condition of stoped engine and underway were obtained 8.30$^{\circ}$, 4.37$^{\circ}$, 8.30$^{\circ}$, 4.37$^{\circ}$, and 5.01$^{\circ}$, 4.36$^{\circ}$, 5.50$^{\circ}$, 5.10$^{\circ}$, respectively. 2. The rates of performance of active mode operations were carried out during a sea trial in the condition of stop engine and underway resulted in 47.5%, 12.7%, respectively, therefore the active mode operation estimated to be improved more than passive mode operation. 3. Active - A.R.T by INTERING Stabilizer didn't affect the amplitude of pitching.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.