• Knowledge Management Research
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• v.23 no.3
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• pp.231-258
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• 2022

As integrated management of scattered knowledge in the organization contributes to organizational performance, organizations are increasing their investment in knowledge management(KM) policies and technologies. For KM to be operated efficiently, the participation of employees performing knowledge-sharing activities is important. This study suggests how shared goal, value congruence, and task interdependence reduce the negative effects of relation and role conflict on the intention to share knowledge. We surveyed workers in organizations that have more than 50 employees and have KM policies, and 381 samples were used for hypothesis testing. As a result of hypothesis testing, we confirmed that a shared goal affects the intention to share knowledge through each of the factors of value congruence, relation conflict, and role conflict. In addition, we confirmed that value congruence and task interdependence moderated conflicts that negatively affected the intention to share knowledge. We identified the conditions that affect the knowledge-sharing activities of employees in terms of individual, organizational, and work structure. Therefore, the results contribute to the establishment of strategies for achieving the performance of the organization's KM.

• Investigative Magnetic Resonance Imaging
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• v.6 no.1
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• pp.28-34
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• 2002

Purpose : The minimum stimulus onset asynchronoy(SOAmin) is one of important experimental parameters for an event-related fMRI experiment designed with the stochastic stimulus. In this study, the most efficient SOAmin is explored for the stronger activation in motor and language tasks with the stimulus designed stochastically. Materials and methods : The event-related fMRI during motor and language tasks were obtained in four normal right-handed subjects. EPI-BOLD sequence is used at 1.5Tesla MR system for the acquisition of event-related fMRI. For each task the subjects are responded for the stimulus' with 2, 3, 4, and 6 seconds SOAmin. The obtained images are processed with SPM99, and the p value is set as 0.05 for the significant activation detection. The Z value and the number of activated pixels are compared for each task. Results : For the motor task, the primary and supplementary motor areas are activated, and for the language task the consistent activated signals are detected in the Broca's. The activated signal is to be stronger for the shorter SOAmin for both motor and language tasks. At primary motor area, the activated signals is the strongest for 3 seconds SOAmin and for the supplementary motor area the result with 2 seconds SOAmin shows the strongest activation. And the result of language task shows the strongest activation at the 2 seconds SOAmin. Conclusion : In the event-related fMRI of motor and language tasks with the stochastically designed stimulus, the 2 or 3 seconds SOAmin is efficient for more activated and clustered activation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• Knowledge Management Research
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• v.23 no.3
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• pp.213-229
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• 2022

This study aimed to reveal factors that contribute to the creation of collective intelligence (CI) and to provide a cornerstone for future studies on this subject. We hypothesized that effects of the complexity and meaningfulness of the task, diversity, openness to experience, independence, decentralization, and the use of information and communication technology (ICT) are preconditions for the creation of CI. To investigate these hypotheses, we surveyed 200 individuals in the research and development-based manufacturing industry and collected a total of 185 valid responses. The results of the analysis showed that the meaningfulness of the task, openness to experience, independence, decentralization, and the use of ICT had positive effects on CI. Both perceived dissimilarity and value diversity had negative effects on CI. When all variables were included, their significance for the creation of CI showed the following order: use of ICT, the meaningfulness of the task, openness to experience, perceived dissimilarity, and value difference. The theoretical and empirical implications of these results were discussed.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.2
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• pp.113-123
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• 2024

Purpose: This study aimed to examine the mediating effect of learning immersion in clinical simulations on the relationship between nursing student learning motivation and achievement in clinical simulation. Methods: This study was conducted using a cross-sectional survey with 184 nursing students from two universities who participated in clinical simulation between September and December 2022. The participants completed a self-administered questionnaire, and the collected data were analyzed using independent an independent t-test, Mann-Whitney U-test, one-way ANOVA, Pearson's correlation coefficient, and multiple regression analysis to identify the mediating effects of learning immersion on the relationship between nursing student learning motivation and achievement. Results: Among the subvariables of nursing student learning motivation, task value and self-efficacy for learning and performance had a significant effect on learning immersion (respectively, β=.36, p=.001; β=.31, p<.001) and learning achievement (respectively, β=.48, p<.001; β=.38, p<.001). With the input of learning motivation variables, the direct effect of learning immersion on learning achievement was significant (β=.20, p=.003), and the effects of learning motivation and task value and self-efficacy on learning achievement was reduced after controlling for learning immersion, which is a mediating variable (respectively, β=.41, p<.001; β=.32, p<.001). The bootstrapping test to confirm the mediating effect of learning immersion was also significant (task value 95% confidence interval [95% CI], 0.02~0.20; self-efficacy 95% CI, 0.01~0.12). Conclusion: The results of this study suggest that simulation educators should consider learners' motivation and immersion when organizing and operating clinical simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.131-140
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• 1996

In this paper, we propose the method that extracts the speech feature using the hearing model through signal precessing techniques. The proposed method includes following procedure ; normalization of the short-time speech block by its maximum value, multi-resolution analysis using the discrete wavelet transformation and re-synthesize using thediscrete inverse wavelet transformation, differentiation after analysis and synthesis, full wave rectification and integration. In order to verify the performance of the proposed speech feature in the speech recognition task, korean digita recognition experiments were carried out using both the dTW and the VQ-HMM. The results showed that, in case of using dTW, the recognition rates were 99.79% and 90.33% for speaker-dependent and speaker-independent task respectively and, in case of using VQ-HMM, the rate were 96.5% and 81.5% respectively. And it indicates that the proposed speech feature has the potentials to use as a simple and efficient feature for recognition task.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.435-447
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• 1996

In this paper, we propose the method that extracts the speech feature using the hearing model through signal processing techniques. The proposed method includes the following procedure ; normalization of the short-time speech block by its maximum value, multi-resolution analysis using the discrete wavelet transformation and re-synthesize using the discrete inverse wavelet transformation, differentiation after analysis and synthesis, full wave rectification and integration. In order to verify the performance of the proposed speech feature in the speech recognition task, korean digit recognition experiments were carried out using both the DTW and the VQ-HMM. The results showed that, in the case of using DTW, the recognition rates were 99.79% and 90.33% for speaker-dependent and speaker-independent task respectively and, in the case of using VQ-HMM, the rate were 96.5% and 81.5% respectively. And it indicates that the proposed speech feature has the potential for use as a simple and efficient feature for recognition task

• Korean Management Science Review
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• v.13 no.3
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• pp.115-128
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• 1996

System usage, the utilization of information technology(IT) by individuals, groups or organizations, is a core variable in IS research. Indeed, there is widespread agreement among researchers that system usage is the primary variable through which IT affects white collar performance because it is a requisite, albeit insufficient, for deriving the benefits of IT. Furthermore, system usage has a notable practical value for managers interested in evaluating the impact of IT. Despite the number of studies of targeted at explaining system usage, there are more areas which required for the verification of system usage. The purpose of this paper is to address, using the Technological Acceptance Model (TAM), the usage pattern of AHP toward the various task in group decision (GD). The result showed that, for the all of the task types, perceived usage (PU) has more effect than perceived ease-of-use(PEU) on the AHP usage. However, more researches are required to generalize the result of this study.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.519-527
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• 2018

The purpose of this convergence study was to examine the effects of smart learning on learner's participation, academic self-efficacy and task value in nursing education. The study was designed using a nonequivalent control group no-synchronized design. The subjects of this study consisted of 86 experimental group and 95 control group who were nursing students. Data were collected from March 2 to June 8. 2018. The data were analyzed using the spss 18.0 program to perform independent t-test. There were not statistically significant differences in learner's participation(t=1.065, p=.288) but were statistically significant differences in academic self-efficacy(t=2.668, p=.008) and task value(t=2.070, p=.040). Therefore, the smart learning was effective in increasing academic self-efficacy and task value for nursing students. The smart learning is expected to be useful as effective teaching and learning strategies in nursing education.

• KIEAE Journal
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• v.4 no.1
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• pp.11-20
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• 2004

Innovative daylighting systems in buildings in various climatic zones around the world have been developed under the IEA SHC Task21. The performance assessment were obtained by monitoring the most systems using full-scale test model rooms or actual buildings under real sky conditions. This study aims to analyze the configuration and monitoring system of the nine Mock-up models of the IEA SHC Task21 comparatively. For the purpose, the geometry of the test rooms (length, width, height, window area, glazed area and occupied), reflectance of walls, floor and ceiling, transmittance of glazing (transmittance for hemispherical irradiation, normal irradiation and U-value) were compared. And equipment for measurement (manufacturer, range, calibration, maximum calibration error, cosine response error, fatigue error), and data acquisition system (manufacturer, type, number of differential analogue input channels, A/D converter resolution in bits, data acquisition software) were also analyzed comparatively. Some findings of these experimental methodology of standard monitoring have been proven to be a valuable one for future assessment of advanced daylighting systems in our country.