141 research outputs found
이태준 문학에 나타난 이상적 공동체주의
No full textPrevious studies on Lee Taejun"s literature place too much importance on form, vague illuminism and nationalism of his novels. In order to overcome the limits of previous studies, this paper aims to examine ideal communalism revealed in Lee Taejun"s literature. Lee Taejun"s early short stories show influence of Oski Sakae(大杉榮)"s mutualism. Sakae(大杉榮)"s mutualism takes the form of an experiment and a collapse of ideal commune in Lee Taejune"s literature. This is noteworthy in that it shows Lee Taejun"s inclination distinguished from KAPF"s literary illuminism. In Lee Taejun"s novels written in the late 1930"s, influence of Uchimura Ganjo(內村監三) and Seongseochosun"(성서조선)"s nonchurch movement appear. This influence seems clear particularly in the Cheongchunmuseong" (청춘무성). The communalism in this work can be fully understood in the context of the influence of the nonchurch movement. Furthermore, this abstract communalism is related to Fascism in Beoleunchangmada"(별은 창마다). Lee Taejune"s change after Korea"s liberation from Japan should be considered, regarding the influence of Henry David Thoreau"s moral Previous studies on Lee Taejun"s literature place too much importance on form, vague illuminism and nationalism of his novels. In order to overcome the limits of previous studies, this paper aims to examine ideal communalism revealed in Lee Taejun"s literature. Lee Taejun"s early short stories show influence of Oski Sakae(大杉榮)"s mutualism. Sakae(大杉榮)"s mutualism takes the form of an experiment and a collapse of ideal commune in Lee Taejune"s literature. This is noteworthy in that it shows Lee Taejun"s inclination distinguished from KAPF"s literary illuminism. In Lee Taejun"s novels written in the late 1930"s, influence of Uchimura Ganjo(內村監三) and Seongseochosun"(성서조선)"s nonchurch movement appear. This influence seems clear particularly in the Cheongchunmuseong" (청춘무성). The communalism in this work can be fully understood in the context of the influence of the nonchurch movement. Furthermore, this abstract communalism is related to Fascism in Beoleunchangmada"(별은 창마다). Lee Taejune"s change after Korea"s liberation from Japan should be considered, regarding the influence of Henry David Thoreau"s moral resistance. Land reform in Nongto"(농토), particularly shows Lee Taejune"s remarkable ideal communalism. In conclusion, ideal communalism of Lee Taejune"s literature is influenced by Oski Sakae(大杉榮)"s anarchism, Uchimura Ganjo(內村監三) and Seongseochosun"(성서조선)"s nonchurch movement, and Henry David Thoreau"s original communalism
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Consumers' attitudes towards product placement in three media : a cross-cultural study of the U.S. and Korea
No full textNo previous study has yet examined attitude toward product placement in the U.S. and Korea together. To fill the gap in a body of product placement literature, the current study was conducted to examine any differences and similarities on consumers' attitude toward product placement in three different media: film, television, and music. Further, a previously unexamined element in the literature, genre, was incorporated. The results suggest that both American and Korean consumers have generally positive attitudes toward product placement in films and television. However, with regard to music, both groups express uncertain opinions towards the product placement practice. In addition, specific product types and media genres are considered especially appropriate or inappropriate for the practice. Implications for practitioners and public policy makers are provided.Advertisin
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No full textFluorescence imaging of tissues offer an essential means for studying biological systems. Autofluorescence becomes a serious issue in tissue imaging under excitation at UV−vis wavelengths where biological molecules compete with the fluorophore. To address this critical issue, a novel class of fluorophores that can be excited at ∼900 nm under two-photon excitation conditions and emits in the red wavelength region (≥600 nm) has been disclosed. The new π-extended dipolar dye system shows several advantageous features including minimal autofluorescence in tissue imaging and pronounced solvent-sensitive emission behavior, compared with a widely used two-photon absorbing dye, acedan. As an important application of the new dye system, one of the dyes was developed into a fluorescent probe foramyloid-β plaques, a key biomarker of Alzheimer’s disease. The probe enabled in vivo imaging of amyloid-β plaques in a disease-model mouse, with negligible background signal. The new dye system has great potential for the development of other types of two-photon fluorescent probes and tags for imaging of tissues with minimal autofluorescence.16
Two-Photon Absorbing Dyes with Minimal Autofluorescence in Tissue Imaging: Application to in Vivo Imaging of Amyloid-beta Plaques with a Negligible Background Signal
No full textFluorescence imaging of tissues offer an essential means for studying biological systems. Autofluorescence becomes a serious issue in tissue imaging under excitation at UV-vis wavelengths where biological molecules compete with the fluorophore. To address this critical issue, a novel class of fluorophores that can :be excited at, similar to 900 nm under two-photon excitation conditions and emits in the red wavelength region (>= 600 nm) has been disclosed. The new pi-extended dipolar dye system, shows several advantageous features including minimal antofluorescence in tissue imaging and pronounced solvent-sensitive emission behavior, compared with a widely used two-photon absorbing dye, acedan. As an important application of the new dye system, one of the dyes was developed into a fluorescent probe for amyloicl-beta plaques, a key biomarker of Alzheimer's disease. The probe enabled in Vivo imaging of amyloid-beta plaques in a disease-model mouse, with negligible background signal. The new dye system has great potential for the development of other types of two-photon fluorescent probes and tags for imaging of tissues with minimal autofluorescence.
a behavioral economics approach to improving citizens' perceptions and drinking of tap water
No full textThesis(Master) --KDI School:Master of Public Management,2018.As of 2013, the average direct drinking rate of tap water in Korea is 5.4%, and the direct and indirect drinking rate is 55.2%. This is lower than the OECD countries such as the US and Japan, which have a direct drinking rate of 55.2% and direct and indirect drinking rates of 70 ~ 80%.
In spite of efforts to replace old water pipes with new ones and introduce high-level water treatment, ‘unprovoked distrust’ has been a major reason of not drinking tab water. This indirectly shows the low trust in the policies implemented by governments and public organizations to improve tap water quality.
In order to substantially increase the tap water drinking rate, it is necessary to increase a number of the SWC project that consumers can experience directly in the target area. The SWC project increased the trust in water policy, and its trust led to changes in people’s behavior toward drinking tab water.
And also applying ‘nudge’ to people who are satisfied or at least dissatisfied with tap water can be effective in increasing tap water drinking.1. Introduction
2. Literature Review
3. Analysis on the problem of past activities and the cause of not drinking tab water
4. Policy Recommendation
5. ConclusionmasterpublishedGon Sung, JEONG
Improvement of P300-Based Brain-Computer Interfaces for Home Appliances Control by Data Balancing Techniques
No full textThe oddball paradigm used in P300-based brain-computer interfaces (BCIs) intrinsically poses the issue of data imbalance between target stimuli and nontarget stimuli. Data imbalance can cause overfitting problems and, consequently, poor classification performance. The purpose of this study is to improve BCI performance by solving this data imbalance problem with sampling techniques. The sampling techniques were applied to BCI data in 15 subjects controlling a door lock, 15 subjects an electric light, and 14 subjects a Bluetooth speaker. We explored two categories of sampling techniques: oversampling and undersampling. Oversampling techniques, including random oversampling, synthetic minority oversampling technique (SMOTE), borderline-SMOTE, support vector machine (SVM) SMOTE, and adaptive synthetic sampling, were used to increase the number of samples for the class of target stimuli. Undersampling techniques, including random undersampling, neighborhood cleaning rule, Tomek's links, and weighted undersampling bagging, were used to reduce the class size of nontarget stimuli. The over- or undersampled data were classified by an SVM classifier. Overall, some oversampling techniques improved BCI performance while undersampling techniques often degraded performance. Particularly, using borderline-SMOTE yielded the highest accuracy (87.27%) and information transfer rate (8.82 bpm) across all three appliances. Moreover, borderline-SMOTE led to performance improvement, especially for poor performers. A further analysis showed that borderline-SMOTE improved SVM by generating more support vectors within the target class and enlarging margins. However, there was no difference in the accuracy between borderline-SMOTE and the method of applying the weighted regularization parameter of the SVM. Our results suggest that although oversampling improves performance of P300-based BCIs, it is not just the effect of the oversampling techniques, but rather the effect of solving the data imbalance problem
Toward an adaptable deep-learning model for satellite-based wildfire monitoring with consideration of environmental conditions
No full textAs the majority of active fire detection algorithms have been developed for worldwide applications using only satellite data without considering observing conditions and environmental factors, their performance varies regionally. This study investigates the viability of an adaptable active fire detection model that is applicable to diverse environmental and observing conditions by fusing numerical model data and satellite images. The model was developed for various land cover and climate types using commonly utilized brightness temperature-related variables (key variables) and supporting variables (sub-variables), including solar zenith angle, satellite zenith angle (SAZ), relative humidity (RH), and skin temperature. A dual-module (DM) convolutional neural network (CNN) structure was adopted to consider the different properties of key variables and sub-variables, and a control without sub-variables was used to assess the impact of observing and environmental variables. The proposed model was further evaluated using existing polar-orbiting and geostationary satellite-based active fire products. The recall and precision of the control model were 0.80 and 0.98, respectively, and the standard deviation of recall for the five focus sites was 0.140. However, the DM CNN model was notable for its higher recall and robustness compared to the control model (recall of 0.84, precision of 0.97, and standard deviation of recall of 0.126). High RH and SAZ, and the day-night transition period contributed to the poor performance of the control model which was mitigated by the DM CNN model. In particular, the use of RH improved the recall of the model, and SAZ contributed to the reduction of performance variation. Our model also outperformed the two geostationary satellite-based active fire products in terms of detection capacity, resulting in a spatial distribution of active fires similar to that of polar-orbiting satellite-based active fire products
Data augmentation effects using borderline-SMOTE on classification of a P300-based BCI
No full textIn this study, we addressed a problem of imbalance in the size of event-related potentials (ERPs) between target and nontarget stimulation events, which is intrinsic to the odd-ball paradigm used in P300-based brain-computer interfaces (BCIs). Specifically, we investigated whether data augmentation could remedy this problem and improve BCI performance. We investigated a data augmentation technique, borderline-Synthetic Minority Over-sampling Technique (SMOTE). We focused on the effects of data augmentation on users with poor BCI performance. The EEG data were obtained from experiments with the P300-based BCI system developed for controlling 3 home appliances (Lamp, Door lock, Bluetooth speaker), where the classifier was designed by a support vector machine (SVM) and a convolutional neural network (CNN). As a result, although Borderline-SMOTE did not significantly change the overall BCI performance, it significantly improved the performance of poor performers. This suggests that data augmentation can offer an effective way to increase the performance of users illiterate to P300-based BCIs
EEG functional network on oddball paradigm: connectivity estimation based on ERP waveforms
No full textIn this study, we analyzed functional connectivity directly from event related potential (ERP) waveforms elicited during the oddball task. We empirically estimated non-rhythmic phases of the temporal unfolding of ERP waveforms, calculated the phase locking index (PLI), and quantified the resulting network topology by extracting minimum spanning tree (MST). Overall PLI is higher in the target condition. Specifically, PLI between right parietal and other areas are significantly higher (paired t-test, p<0.05) than those in nontarget condition. According to MST metrics,target ERPs revealed higher degree, higher leaf fraction, lower kappa and larger mean weight (paired t-test, p <0.05).The results showed that target ERPs resulted in higher connectivity
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