This study was conducted to determine the appropriate seeding dates by verifying the difference in winter survival and productivity of alfalfa according to fall sowing dates in the central area of South Korea. The experiment was conducted for 2 years (2020 and 2021) at the field in the Department of Animal Resources Development, NIAS located in Cheonan. Sowing dates started from September 18 to November 8 with 10 days of intervals during 2020 and 2021; SO1 (September 18), SO2 (September 28), SO3 (October 8), SO4 (October 18), SO5 (October 28), and SO6 (November 8). After sowing, the winter survival rate was measured in the spring of the following year, and the dry matter yield was measured by harvesting at 10% flowering and harvesting five times a year. SO6 failed to winter survival, and SO5 also had a lower winter survival rate than SO1~4 (p<0.05). The average annual dry matter yield of alfalfa linearly decreased with delaying sowing dates (p<0.05). The feed value did not differ in the same year by delaying the sowing date in the same year. These results suggest that sowing date should be started before October 18 to increase winter survival and productivity of alfalfa in the central area of South Korea.

Civil defense originally refers to the protection of civilians in the events of war-related disasters. Today, it encompasses a wide range of protection, rescue, and recovery activities not only aimed at minimizing the damage caused by war but also addressing natural and man-made disasters such as wildfires, typhoons, and floods. Civil defense uniforms are worn by volunteers who participate in civil defense training organized by practitioners, government officials, and military personnel. Therefore, more than 3,350,000 persons (+6.5 % of the Korean population) likely should wear civil defense uniforms. As such, the functionalities of civil defense uniforms need to be reexamined and improved in response to the wider and newer responsibilities of the civil defense system to protect the civil defense personnel from potential hazards and to help better serve the Korean citizens. The essential functions of civil defense uniforms were proposed by analyzing various civil defense activities. Per the level and type of safety hazards, the design and materials for civil defense uniforms should ideally differ, similar to civil defense uniforms in other countries. We surveyed the current Korean civil defense uniforms’ design, material compositions and important functionalities such as water repellency, water pressure resistance, and flame resistance. Compared to common functional workwear, we suggest room for improvement in the functional properties of civil defense uniforms. This research paves a new road for the functional design of civil defense uniforms to address a wider range of hazards, potentially leading to rational guidelines for protective workwear and government uniform development.

A typical consumer is exposed to more than 5,000 advertisements per day (Story 2015) by exposure to around 500 advertising messages before ending breakfast (Marshall, 2015), and it is impossible for consumers to remember most of the advertisement images and messages. Thus, one consistent yet not thoroughly investigated question for advertisers is how advertisers draw consumers' attention by differentiating their brand from competitors' brands. One suggestion from academia is making more "creative" advertising (Dahlén et al., 2008; Lehnert et al., 2014; Rosengren et al., 2013; Smith et al., 2008). However, it is still questionable the exact meaning of "advertising creativity," and the effects of creative advertising on consumer evaluation have not been fully investigated the effects of creativity in advertising evaluation by considering various boundary conditions. The objective of this research is to redefine advertising creativity, to understand how advertising creativity shapes consumers' evaluation, and how these effects are moderated by the different types of boundary conditions, such as industry category, by analyzing more than 100,000 advertising images and copies using a cutting-edge transfer learning technique. The results of the transfer learning algorithm indicate that both cognitive dimensions (e.g., novelty of image) and affective dimensions (e.g., awe and coolness) simultaneously affect the consumers' perception of the advertising creativity, and the current algorithm enables to detect of creative advertising image with 92% accuracy rate.

Social media have emerged as one of the most important tools for firms to engage customers (e.g., Chandrasekaran et al., 2022; Cheng & Edwards, 2015; Lee et al., 2018; Wedel & Kannan, 2016). Within the tourism industry, scholars have investigated the role of social media communication in various contexts, such as online travel information search (Xiang & Gretzel, 2010), sharing travel experiences (So et al., 2018; Wang et al., 2022) and establishing positive customer relationships (Jamshidi et al., 2021). Insights into which social media content makes for generating positive engagement are, however, still largely based on marketers’ intuitions or focusing on message factors of social media posts such as message appeals (e.g., Wang & Lehto, 2020). It also often neglects the importance of the visual component of social media posts, and only a few research have investigated the effects of the image in social media on the travel industry (e.g., Fusté-Forné, 2022). The objective of this research is, therefore, to understand how textual features and image features generate user engagement in social media utilizing cutting-edge transfer learning techniques and to propose how these features should be customized to maximize user engagement for online travel shopping companies. We collect and analyze more than 10,000 Instagram posts from three online travel shopping companies, including Expedia, Priceline, and Kayak. The results from transfer learning algorithms utilizing 24 features, such as the number of people in the image, emotions expressed in the people in the image, hue, and RGB value, successfully predict the level of engagement measured by the number of likes and comments.

For the commercialization of hydrogen energy, a technology enabling safe storage and the transport of large amounts of hydrogen is needed. Porous materials are attracting attention as hydrogen storage material; however, their gravimetric hydrogen storage capacity (GHSC) at room temperature (RT) is insufficient for actual use. In an effort to overcome this limitation, we present a N-doped microporous carbon that contains large proportion of micropores with diameters below 1 nm and small amounts of N elements imparted by the nitrogen plasma treatment. The N-doped microporous carbon exhibits the highest total GHSC (1.59 wt%) at RT, and we compare the hydrogen storage capacities of our sample with those of metal alloys, showing their advantages and disadvantages as hydrogen storage materials.

본 연구는 간 담도기 이미지에서 CAIPIRINHA, 압축 센싱(CS), 딥러닝(DL) 기법을 비교하여 주관적 영상의 질과 국소병변 을 평가하였다. 후향적 연구로 간 담도기 이미지를(획득 시간, CAIPIRINHA 16초, DL 11초, CS 15초; 절편두께, 3mm, 3mm, 1.5mm) 포함한 가도세틱산 조영증강 자기공명영상을 시행한 51명의 환자에서 3개의 이미지와 국소 간 병변은 주관적 이미지 질 평가를 분석하였다. 간 가장자리 선명도는 CAIPIRINHA(3.9±0.8), DL(4.5±0.6), CS(4.5±0.8), 호흡에 의한 운동 허상은 CAIPIRINHA(4.3±0.9), DL(4.7±0.6), CS(4.5±0.8)를 보였다. 21명 환자의 48개 병변에서, 가장자리 선예 도는 CAIPIRINHA(4.3±0.7), DL(4.5±0.6), CS(4.6±0.5), 선명도는 CAIPIRINHA(4.4±0.7), DL(4.7±0.5), CS (4.7±0.5)을 보였다. DL은 검사 시간을 줄이면서 CAIPIRINHA와 비슷한 질을 보이고 호흡 허상을 줄일 수 있다. CS는 얇은 절편 영상의 획득이 가능하여 비슷한 영상의 질을 보여 선택적으로 유용하게 사용할 수 있다.

The large rectangular and cylindrical concrete drums are stored in nuclear power plant (NPP) for a long time. At the early stage of NPP operation, the treatment technology of boron concentrates and spent resin was not well developed, when compared to current system. Since the waste acceptance criteria (WAC) of the disposal facility was not established, the boron concentrates and spent resins were packaged in 200 L drum. Some of the 200 L drums, which contain relatively high dose rate radioactive waste, were stored in large concrete drum. The concrete drum offers superior shielding effect and allows reduction of radiation exposure to workers. The WAC requires various characteristics: radiological characteristics, physical characteristics, chemical characteristics, etc. The non-destructive method allows the rapid evaluation and estimation of the concrete structure. Also, it is expected that the large concrete exhibits integrity after the measurements. In this paper, the non-destructive method to understand the large rectangular and cylindrical drum is systematically studied. The advantage and disadvantage of the non-destructive methods were compared in this paper. In addition, the optimized methodology to characterize the radioactive waste containing large rectangular and cylindrical drum will be discussed in this paper.

A radioactive waste repository consists of engineered barriers and natural barriers and must be safely managed after isolation. Geologic events in natural barriers should be categorized and evaluated according to their magnitude to assess the present and future stability of disposal. Among the longterm evolutionary elements of natural barriers, faults are a small portion of the Earth’s crust. Still, they play an important role in nuclide transport as conduits for fluids moving deep underground. In addition, the physical and chemical properties of fault rocks are useful for understanding the longterm and short-term behavior of faults. Paleomagnetic research has been used extensively and successfully for igneous, metamorphic, and sedimentary rocks. In addition, magnetic characterization of fault rocks can be used to describe faults or infer the timing of major geological events along fault zones. Components of magnetization defined in fault-breccias were attributed to chemical processes associated with hydrothermal mineralization that accompanied or post-dated tectonic activity along the fault. The study of magnetic minerals in fault rocks can be used as “strain indicators”, “geothermometers”, etc. This study is a preliminary test of magnetic properties using fault gouges. Fault gouges are not well preserved in typical terrestrial environments. Access to fresh gouges typically requires trenching through faults or sampling with a core drill. Fortunately, it is a magnetic property study using a fault gouge that exists on the inner wall of KURT (KAERI Underground Research Tunnel). This is to identify the motion history of the fault and, furthermore, to understand the stress structure at the time of fault creation. In addition, it can be presented as evidence for evaluating faults that may appear in future URL (Underground Research Laboratory).

In KAERI, a site descriptive model for stress field estimation had already been constructed by using integrated field data within KURT site scale. A sub-divided rock block domain containing major fracture zones has spatial rock mass and fault properties. The properties were decided based on the rock classification results of several borehole investigations. Modeling for maximum and minimum horizontal stress field estimation was performed and compared with the in-situ data. As a result, a depth-dependent stress ratio was adopted to obtain numerical results closer to actual in-situ data. Although the results were suitable at a relatively low depth (~500 m), there is still some deviation trend at a deep depth. This study aims to improve these modeling results by incorporating not only depth-dependent stress ratio but also changes in rock mass properties along the depth. The deep borehole of DB2 in the KURT site indicated fracture distribution corresponding to the property changes. Natural fractures are typically randomly oriented, and the fracture frequency decreases with increasing depth. The increase in P-wave velocity log data accompanies these features. A discrete fracture network (DFN) model can be used to simulate fractured rock explicitly, but DFN modeling is not feasible for site scale analysis because of its numerical efficiency. Therefore, as a preliminary model in this study, the effect of fracture distribution was considered by substituting the influence for the depth-dependent property. The properties were estimated from the fracture frequency and P-wave velocity log data. The influence of elastic modulus and density on the site stress field was dominant, with decreasing the deviation trend between modeling and in-situ data at a deep depth. Considering that the depth of the repository construction is within about 500 m, it may not be necessary to consider the change of rock properties with depth. However, it was determined that the rock property effect might need to be considered when the loading conditions change due to subsidence in the long-term evolution scenario. Continuously, this site descriptive modeling will be interdependently conducted with a representative DFN block model for deriving equivalent properties in fractured rock.

The distribution characteristics of rock fractures determine the hydro-mechanical behavior of natural barriers. Rock fractures are defined by various parameters, which are analyzed as the probability distribution from observation results by surveying the exposed rock surface or borehole. The size is known to have the most uncertainty among the fracture parameters because it cannot be directly measured. Therefore, various estimation methods have been proposed for fracture size distribution using the fracture traces observable on the rock surface. However, most methods are based on a planar survey area, limiting their applicability to the underground research laboratory (URL) excavated in the form of tunnels. This study aims to review a method that can be applied to estimate the size distribution of fractures in deep rock masses at the URL site. The estimation method using the joint center volume (JCV) has recently been extended to be applicable regardless of the geometry of the survey area, which means that it can be applied to the URL site with complex structures. To apply the JCV-based estimation method to non-planar survey areas, JCV calculation using Monte Carlo simulation and estimation of fracture size distribution using the maximum likelihood method are required. In this study, we applied the JCV-based estimation method to a tunnel-shaped survey area to examine its applicability to the URL site. The error rates were analyzed when there were fracture sets with various orientations, size distributions, and maximum fracture sizes in the rock mass, and it was found to be less than 10% in all cases. This result indicates that the JCV-based estimation method can be used to estimate the fracture size distribution of the surrounding rock mass if accompanied by a reliable survey of fracture traces on the tunnel surface inside the URL site. Also, since there are no restrictions on the geometry of the survey area, we can continuously update the estimation results during the URL excavation process to increase reliability. The fracture size distribution is essential for constructing the discrete fracture network (DFN) model of the rock mass units at the URL site. In the future, the uncertainty for the fracture size in the DFN model is expected to be reduced by applying the JCV-based estimation method.

As regulations on carbon emissions increase, the interest in renewable energy is also increasing. However, the efficiency of renewable energy generation is highly low and has limitations in replacing existing energy consumption. In terms of this view, nuclear power generation is highlighted because it has the advantage of not emitting carbon. And accordingly, the amount of spent nuclear fuel is going to increase naturally in the future. Therefore, it will be important to obtain the reliability of containers for transporting safely and storing spent nuclear fuel. In this study, a method for verifying the integrity and airtightness of a metal cask for the safe transportation and storage of spent nuclear fuel was studied. Non-destructive testing, thermal stability, leakage stability, and neutron shielding were demonstrated, and as a result, suitable quality for loading spent nuclear fuel could be obtained. Furthermore, it is meaningful in that it has secured manufacturing technology that can be directly applied to industrial field by verifying actual products.