• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.91-116
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• 2019

This study conducted a demand analysis for the operation and management of closed schools, the direction of future use of closed schools, and the utilization of closed schools, among local residents expected to play a key role in the successful use of closed libraries. According to the study, residents in areas where schools actually occur may actively consider the use of closed schools when they are lacking in the number of libraries in the region or when they hope to remodel their schools as libraries, given that they are positive about future use of closed schools and that remodeling them is more economical in terms of cost than building new libraries. The current awareness of the use and operation of closed schools remains at a normal level, so it is deemed necessary to improve the direction of the promotion, operation and recycling of closed schools in the order of promotion, operation and physical aspects by grouping obstacles to the operation and management of closed schools. In addition, the current status of cultural facilities and the demands of local residents are met in terms of the types of use of closed school facilities, and it means that closed schools can be used in a relatively easy-to-access location based on their location, while libraries can be used as a space for cultural facilities that are different from the existing public libraries, exhibition halls, and eco-friendly libraries.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.1-13
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• 2011

Cheongpyeongsa Temple was originally built in the early years of Goryeo Dynasty, but its current structural framework was made by the Lord Jinrakgong Lee Ja Hyeon(1061-1125) of the middle Goryeo period based on the Zen thought after he began living in the Cheongpyeong mountain around the temple in 1089. The purpose of this study is to conceptualize, based on old documents, historical changes of the appearance and survival of man-made structures with in the Zen garden formed and developed after Lee Ja Hyeon laid the foundation for Munsuwon Zen garden. Among the eight, outside-the-temple hermitages built at the time of Lee Ja Hyeon's Munsuwon Zen garden, only three hermitages, which are Sik-am, Gyeonseong-am, Yangshin-am had been remaining thanks to restoration and repair until late Joseon Dynasty and preserved as symbolic hermitages. Also, the Yeongji Pond built at the time of Lee Ja Hyeon still remains as precious landscape relics which is meaningful as a genuine Goryeo-period pond. The nine pine trees said to be planted by Lee Ja Hyeon remained until middle 1800s through their descendant trees. When the Buddhist monk Bowoo Daesa(1509-1565)changed the name to Cheongpyeongsa Temple in middle Joseon based on the Munsuwon Zen garden built by Lee Ja Hyeon and greatly expanded it, he newly built and expanded all buildings inside the temple except for Neunginjeon(main temple building), resulting in the present temple structure. In addition, by greatly enhancing the level of scenery by reconstructing Yeongji Pond outside the temple area and transplanting garden plants from the royal court, he made Cheongpyeongsa Temple the most prosperous Zen garden in its history. But after the mid-1800s, which is late Joseon period, Cheongpyeongsa Temple failed to thrive further and began to decline, and so currently most buildings of the Zen garden have disappeared except for some parts of the temple and other facilities are neglected.

• Journal of International Area Studies (JIAS)
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• v.14 no.4
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• pp.27-52
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• 2011

The regions of Central Asia have each acquired an elevated strategic importance in the new security paradigm of post-September 1lth. Comprised of five states, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, Central Asia's newly enhanced strategic importance stems from several other factors, ranging from trans-national threats posed by Islamic extremism, drug production and trafficking, to the geopolitical threats inherent in the region's location as a crossroads between Russia, Southwest Asia and China. Although the U.S. military presence in the region began before September 11th, the region became an important platform for the projection of U.S. military power against the Taliban in neighboring Afghanistan. The analysis goes on to warn that 'with US troops already in place to varying extents in Central Asian states, it becomes particularly important to understand the faultlines, geography, and other challenges this part of the world presents'. The Kyrgyz military remains an embryonic force with a weak chain of command, the ground force built to Cold War standards, and an almost total lack of air capabilities. Training, discipline and desertion - at over 10 per cent, the highest among the Central Asian republics - continue to present major problems for the creation of combat-effective armed forces. Kyrgyzstan has a declared policy of national defence and independence without the use of non-conventional weapons. Kyrgyzstan participates in the regional security structures, such as the Collective Security Treaty Organisation (CSTO) and the Shanghai Co-operation Organisation (SCO) but, in security matters at least, it is dependent upon Russian support. The armed forces are poorly trained and ill-equipped to fulfil an effective counter-insurgency or counter-terrorist role. The task of rebuilding is much bigger, and so are the stakes - the integrity and sovereignty of the Kyrgyz state. Only democratization, the fight against corruption, reforms in the military and educational sectors and strategic initiatives promoting internal economic integration and national cohesion hold the key to Kyrgyzstan's lasting future

• Animal Bioscience
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• v.36 no.10
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• pp.1488-1498
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• 2023

Objective: α_S1-Casein is more closely associated with milk allergic reaction than other milk protein components. microRNA (miRNA) is a class of small non-coding RNAs that modulate multiple biological progresses by the target gene. However, the post-transcriptional regulation of α_S1-casein expression by miRNA in ruminants remains unclear. This study aims to explore the regulatory roles of miR-380-3p on α_S1-casein synthesis in goat mammary epithelial cells (GMEC). Methods: α_S1-Casein gene and miR-380-3p expression was measured in dairy goat mammary gland by quantitative real-time polymerase chain reaction (qRT-PCR). miR-380-3p overexpression and knockdown were performed by miR-380-3p mimic or inhibitor in GMEC. The effect of miR-380-3p on α_S1-casein synthesis was detected by qRT-PCR, western blot, luciferase and chromatin immunoprecipitation assays in GMEC. Results: Compared with middle-lactation period, α_S1-casein gene expression is increased, while miR-380-3p expression is decreased during peak-lactation of dairy goats. miR-380-3p reduces α_S1-casein abundance by targeting the 3'-untranslated region (3'UTR) of α_S1-casein mRNA in GMEC. miR-380-3p enhances β-casein expression and signal transducer and activator of transcription 5a (STAT5a) activity. Moreover, miR-380-3p promotes β-casein abundance through target gene α_S1-casein, and activates β-casein transcription by enhancing the binding of STAT5 to β-casein gene promoter region. Conclusion: miR-380-3p decreases α_S1-casein expression and increases β-casein expression by targeting α_S1-casein in GMEC, which supplies a novel strategy for reducing milk allergic potential and building up milk quality in ruminants.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.794-801
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• 2023

The high seas, covering the majority of the world's oceans, hold invaluable marine resources crucial for the growth of the marine bio-industry. The High seas bioresources program of South Korea is at the forefront of these global efforts. This study aims to gauge public awareness and quantify the project benefits, offering insights for future policy decisions. The results revealed that the estimated annual average willingness to pay (WTP) was 3,778.8 KRW, equating to approximately 81.54 billion KRW when extrapolated to the entire national population. The implications of the study are twofold: The project benefits, based on WTP, are substantial, amounting to approximately 81.5 billion KRW annually. This provides critical reference material for future policy formulation, given the considerable WTP in comparison to the current investment. Although interest in international sea marine biological resources is growing, public awareness remains relatively low. However, the project plays a crucial role in building essential databases for the marine bio-industry and securing international sea marine biological resources. Public interest and sustained support are pivotal, not only for this project but also for future policy implementation. Strategies to enhance public awareness are essential, and the study results offer valuable input for future policy decisions.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.

• Industry Promotion Research
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• v.9 no.2
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• pp.69-75
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• 2024

Korea has entered the ranks of advanced countries in terms of economic size and technological competitiveness. However, its industrial accident fatality rate remains among the lowest in OECD countries, and recent incidents such as various building collapses have resulted in numerous deaths of workers or citizens, reminiscent of accidents in developing countries. According to the 2022 Industrial Accident Status Analysis by the Ministry of Employment and Labor, out of the 874 fatalities in work-related accidents in 2022 across all industries, 402 were in the construction industry, accounting for approximately 46% of all fatalities. In particular, the construction industry's fatality rate stands at 1.61, significantly higher than the overall industry fatality rate of 0.43, indicating its severity. Construction ranks highest in terms of fatality rates, with mining at 12.18 and fishing at 1.80. When categorizing construction projects into private and public, private projects show significantly higher figures in terms of contracts, contract amounts, accident numbers, and fatalities compared to public projects. However, unlike public agencies, many private clients lack adequate safety and health activities and lack established safety and health systems. This study aims to raise awareness among private clients about the need to establish safety and health systems and enhance safety and health activities, and to discuss the direction of future development of advanced safety and health practices among private clients.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.173-182
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• 2024

In recent, there has been a trend toward primarily utilizing data-driven models employing artificial intelligence technologies, such as machine learning, for flood prediction. These data-driven models offer the advantage of utilizing pre-training results, significantly reducing the required simulation time. However, it remains that a considerable amount of flood data is necessary for the pre-training in data-driven models, while the available observed data for application is often insufficient. As an alternative, validated simulation results from physically-based models are being employed as pre-training data alongside observed data. In this context, we developed a flood mapping accelerator to generate flood maps for pre-training. The proposed accelerator automates the entire process of flood mapping, i.e., estimating flood discharge using HEC-1, calculating water surface levels using HEC-RAS, simulating channel overflow and generating flood maps using RAS Mapper. With the accelerator, users can easily prepare a database for pre-training of data-driven models from hundreds to tens of thousands of rainfall scenarios. It includes various convenient menus containing a Graphic User Interface(GUI), and its practical applicability has been validated across 26 test-beds.