• Psychiatry investigation
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• v.15 no.11
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• pp.1019-1029
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• 2018

Objective We investigated how mental health awareness among North Korean refugees transformed depending on temporal-spatial context changes. Methods In 2013, we conducted interviews with 10 refugees (eight women) who had been in South Korea for over a year and performed a qualitative analysis of the change in mental health awareness in the differences between living in North Korea, escape (a related period of forced sojourn in a third country), and settlement in South Korea. Results We classified 39 concepts into five main categories. The first two categories (while living in North Korea) were "a mindset for the system, but not for individual mental health" and "being confined in a social environment that was indifferent to mental health." A third category appeared during escape: "focusing on survival amid continuity of intense suffering." The final two categories appeared when settling in South Korea: "recognition of mental health amid cultural shock" and "introspection and sorting oneself out." Conclusion This qualitative study enabled a better multi-dimensional understanding of the social and cultural aspects involved in improving mental health awareness among North Korean refugees in South Korea. It is desirable to integrate mental health as a part of daily life and to expand training for North Korean settlers.

• Journal of the Korean Society of Food Culture
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• v.37 no.3
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• pp.179-195
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• 2022

For any research study, in order to achieve the researcher's intended purpose, the depth of research is added, and the area of the subject is expanded by clearly defining the scope and objective. The study was undertaken to analyze the bibliographic data of 254 papers in the field of foodservice and restaurant published in the Journal of the Korean Dietary Culture from 2002 to 2021. The study was divided into two periods: 2002 to 2011, and 2012 to 2021. Research topics were derived and research trends according to temporal changes were confirmed through analysis of keyword networks by period. In addition, analyzing the keyword network of simultaneous appearance of "foodservice" and "restaurant", the research topics were compared and analyzed in relation to which keywords were expanded by period. Our analysis revealed that the research topics were mostly studied for satisfaction and nutrition. Additionally, they were classified into procurement, Korean food before employee menu, marketing, restaurant industry, and quality. In the period from 2002 to 2011, it was confirmed that studies encompassed a wide range of research topics, focusing on foodservice and restaurant; in the second period from 2012 to 2021, the research topics were more classified and subdivided.

• Applied Chemistry for Engineering
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• v.33 no.1
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• pp.17-27
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• 2022

Fluorescence imaging is widely used to image cells or small animals due to its high temporal and spatial resolution. Because conventional fluorescence imaging uses visible light, the penetration depth of light within the tissue is low, phototoxicity may occur due to visible light, and the detection sensitivity is lowered due to interference by background autofluorescence. In order to overcome this limitation, long-wavelength light should be used, and fluorescence imaging using near-infrared-I (NIR-I) in the region of 700~900 nm has been developed. To further improve imaging quality, researchers are interested in using a longer wavelength light, near-infrared-II (NIR-II) ranging from 1000 to 1700 nm. In the NIR-II region, light scattering is further minimized, and the penetration depth of light in the tissue is improved up to about 10 mm, and autofluorescence of the tissue is reduced, enabling high sensitivity and resolution fluorescence imaging. In this review, among various NIR-II fluorescence imaging probes, inorganic nanoparticle-based probes with excellent photostability and easily tunable emission wavelength were described, focusing on single-walled carbon nanotubes, quantum dots, and lanthanide nanoparticles.

• Informatization Policy
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• v.29 no.4
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• pp.67-90
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• 2022

The March 2022 presidential election held at the peak of the COVID-19 pandemic drew flak for undermining the principle of universal suffrage by failing to guarantee properly the voting rights of confirmed and quarantined persons. Guaranteeing their voting rights requires thinking about e-voting that can fundamentally overcome the temporal and spatial limitations of current paper voting polling stations. The question is how to deal with the increased possibility of contradicting or violating the principles of equality and direct and secret suffrage due to the expansion of universal suffrage. In order to obtain implications for this, we looked at the case of Estonia, which has been holding 11 national elections without any problems since the introduction of e-voting in 2005. Estonia was successfully building trust in the system, government, and society through the institutionalization and routinization of the overall socio-technical system of e-voting, along with political and constitutional agreements on the principles of elections. Therefore, we should not only consider the possibility of e-voting in terms of technological development and level but also discuss the establishment of trust by mediating conflicts between election principles from a normative point of view to reach a social consensus.

• The Journal of the Society of Stroke on Korean Medicine
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• v.14 no.1
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• pp.1-7
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• 2013

The following study reviewed the walking patterns of stroke patients with hemiplegia, which is called hemiplegic gait of stroke patients. Focusing is given to the changes in the distance and temporal factors of walking, which is called spatiotemporal characteristics, throughout the walking cycle. First, we introduced the definitions of essential terms related to gait and its measure. Second, we reviewed the spatiotemporal characteristics of hemiplegic gait. A main issue was that hemiplegic gait showed significant deviations from normal healthy gait. Although hemiplegia is primarily associated with unilateral motor disorder, changes in almost all spatiotemporal parameters used to assess walking were evident on both the involved and uninvolved sides of the body. Last, we reviewed the changes of spatiotemporal parameters of hemiplegic gait according to the prognosis or status of stroke patients, which may help to give a specific intervention for rehabilitation of stroke.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.57-69
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• 2024

Crop classification plays a vitalrole in monitoring agricultural landscapes and enhancing food production. In this study, we explore the effectiveness of Long Short-Term Memory (LSTM) models for crop classification, focusing on distinguishing between apple and rice crops. The aim wasto overcome the challenges associatedwith finding phenology-based classification thresholds by utilizing LSTM to capture the entire Normalized Difference Vegetation Index (NDVI)trend. Our methodology involvestraining the LSTM model using a reference site and applying it to three separate three test sites. Firstly, we generated 25 NDVI imagesfrom the Sentinel-2A data. Aftersegmenting study areas, we calculated the mean NDVI values for each segment. For the reference area, employed a training approach utilizing the NDVI trend line. This trend line served as the basis for training our crop classification model. Following the training phase, we applied the trained model to three separate test sites. The results demonstrated a high overall accuracy of 0.92 and a kappa coefficient of 0.85 for the reference site. The overall accuracies for the test sites were also favorable, ranging from 0.88 to 0.92, indicating successful classification outcomes. We also found that certain phenological metrics can be less effective in crop classification therefore limitations of relying solely on phenological map thresholds and emphasizes the challenges in detecting phenology in real-time, particularly in the early stages of crops. Our study demonstrates the potential of LSTM models in crop classification tasks, showcasing their ability to capture temporal dependencies and analyze timeseriesremote sensing data.While limitations exist in capturing specific phenological events, the integration of alternative approaches holds promise for enhancing classification accuracy. By leveraging advanced techniques and considering the specific challenges of agricultural landscapes, we can continue to refine crop classification models and support agricultural management practices.

• Journal of Astronomy and Space Sciences
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• v.40 no.3
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• pp.101-111
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• 2023

We conducted a statistical study of polar mesospheric summer echoes (PMSEs) in relation to magnetic local time (MLT), considering the geomagnetic conditions using the K-index (or K). Additionally, we performed a case study to examine the velocity profile, specifically for high velocities (≥ ~100 m/s) varying with high temporal resolution at high K-index values. This study utilized the PMSE data obtained from the mesosphere-stratosphere-troposphere radar located in Esrange, Sweden (63.7°N, 21°E). The change in K-index in terms of MLT was high (K ≥ 4) from 23 to 04 MLT, estimated for the time PMSE was present. During the near-midnight period (0-4 MLT), both PMSE occurrence and signal-to-noise ratio (SNR) displayed an asymmetric structure with upper curves for K ≥ 3 and lower curves for K < 3. Furthermore, the occurrence of high velocities peaked at 3-4 MLT for K ≥ 3. From case studies focusing on the 0-3 MLT period, we observed persistent eastward-biased high velocities (≥ 200 m/s) prevailing for ~18 min. These high velocities were accompanied with the systematic motion of profiles at 85-88 km, including large shear formation. Importantly, the rapid variations observed in velocity could not be attributed to neutral wind effects. The present findings suggest a strong substorm influence on PMSE, especially in the midnight and early dawn sectors. The large zonal drift observed in PMSE were potentially energized by local electromagnetic fields or the global convection field induced by the electron precipitation during substorms.

• Smart Media Journal
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• v.13 no.2
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• pp.156-164
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• 2024

The Metaverse as a combination of physical and digital space, provides many consumers with a different process of search, evaluation, consumption, and disposal than before, based on hyper-connected and hyper-realistic services. Therefore, it is necessary to examine what kind of sensory experiences customers feel when performing various activities in the Metaverse and how these experiences affect customers' behavioral responses. This study measured the temporal and emotional experience of the Metaverse service environment felt during the Metaverse experience journey of customers experiencing medical tourism services. The results of the study showed that the emotional experience through Metaverse had a more positive impact on customer satisfaction and customer loyalty as the intensity of the Metaverse experience deepened. In particular, it was confirmed that the emotional experience at the end of the Metaverse service had a positive influence on repurchase behavior. These results show that, just as in the real world, customer experience in the Metaverse can provide important insight into understanding customers' post purchase behavior and how service providers can develop and implement effective customer experience strategies in the Metaverse environment.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.411-421
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• 2010

A time-reversal mirror (TRM) is useful in diverse areas, such as reverberation ing, target echo enhancement and underwater communication. In underwater communication, the bit error rate has been improved significantly due to the increased signal-to-noise ratio by spatio-temporal focusing. This paper deals with two issues. First, the optimal number of array elements for a given environment was investigated based on the exploitation of spatial diversity. Second, an algorithm was developed to determine the optimal location of the given number of array elements. The formulation is based on a genetic algorithm maximizing the contrast between the foci and area of interest as an objective function. In addition, the developed algorithm was applied to the matched field processing with ocean experimental data for verification. The sea-going data and simulation showed almost 3 dB improvement in the output power at the foci when the array elements were optimally distributed.