• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.22-37
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• 2020

We analyze the comprehensive three-dimensional (3D) magnetic structure characteristics from the seafloor to the deep layer of the Tofua Arc (TA) 12 seamount in the Tonga Arc, Southwestern Pacific, using bathymetric and geomagnetic data, and magnetization vector inversion (MVI) results. The seafloor features surrounding TA 12 highlight a NW-SE-oriented elliptical caldera at the summit of the seamount, two small cones in the depressed area. A large-scale sea valley is present on the western flank of the seamount, extending from these caldera cones to the southwestern base of the seamount. TA 12 seamount exhibits a low magnetic anomaly in the caldera depression, whereas a high magnetic anomaly is observed surrounding the low magnetic anomaly across the caldera summit. It is therefore presumed that there may be a strong magnetic material distribution or magma intrusion in the caldera. The 3D MVI results show that the high anomaly zones are mainly present in the surrounding slopes of the seamount from the seafloor to the -3,000 m (below the seafloor) level, with the magnetic susceptibility intensity increasing as the seafloor level increases at the caldera depression. However, small high anomaly zones are present across the study area near the seafloor level. Therefore, we expect that the magma ascent in TA 12 seamount migrated from the flanks to the depression area. Furthermore, we assume that the complex magnetic distribution near the seafloor is due to the remnant magnetization.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.42 no.2
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• pp.103-109
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• 2016

Efficacy of cosmetics has been mainly evaluated by qualitative and quantitative methods based on visual sense, tactile sense and skin structure until now. In this study, we suggested a novel evaluation method for skin status based on sound; measuring and analyzing the rubbing noise generated by applying cosmetics. First, the rubbing noise was measured at a close range by a high-sensitivity microphone in anechoic environment, and the noises were analyzed by 1/3 octave band analysis in frequency-domain. Three conditions, 1) before washing, 2) after washing and 3) after application of cosmetics, were compared. As a result, sound pressure level (SPL) of rubbing noise after washing was larger than that of before washing, and the SPL of rubbing noise after cosmetic application was the smallest. Furthermore, the energy of rubbing noise after application was higher than that of the before and after washing conditions in a low frequency band (lower than 2 kHz region). Conversely, the energy of rubbing noise after application was much lower than the others in a high-frequency band (upper than 2 kHz region). This change of energy distribution was described as a balloon-skin model. High SPL in the low frequency region after the cosmetic applications was due to the increase of "flexibility index", while SPL in the high frequency region significantly decreased because of the attenuation which is related to "softness index". Therefore, we developed two indices based on the spectrum-energy difference for evaluating skin conditions. This proposed method and indices were verified via skin flexibility and roughness measurement using cutometer and primos respectively. These results suggest that acoustic measurement of skin friction noise may be a new skin status evaluation method.

• Journal of Science and Technology Studies
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• v.19 no.1
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• pp.1-51
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• 2019

The understanding of law and science as fundamentally different two systems, in which fact stands against justice, rapid progress against prudent process, is far too simple to be valid. Nonetheless, such account is commonly employed to explain the tension between law and science or justice and truth. Previous STS research raises fundamental doubts upon the off-the-shelf concept of "scientific truth" that can be introduced to the court for legal judgment. Delimiting the qualification of the expert, the value of the expert knowledge, or the criteria of the scientific expertise have always included social negotiation. What are the values that are affecting the boundary-making of the thing called "modern science" that is supposedly useful in solving legal conflicts? How do the value of law and the meaning of justice change as the boundaries of modern science take shapes? What is the significance of "science" when it is emphasized, particularly in relation to the legal provisions of paternity, and how does this perception of science affect unfoldings of legal disputes? In order to explore the answers to the above questions, we follow a process in which a type of "knowledge-deficient model" of a court-that is, law lags behind science and thus, under-employs its useful functions-can be closely examined. We attend to a series of discussions and subsequent changes that occurred in the US courts between 1930s and 1970s, when blood type tests began to be used to determine parental relations. In conclusion, we argue that it was neither nature nor truth in itself that was excavated by forensic scientists and legal practitioners, who regarded blood type tests as a truth machine. Rather, it was their careful practices and crafty narratives that made the roadmaps of modern science, technology, and society on which complex tensions between modern states, families, and courts were seen to be "resolved".

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.535-543
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• 2022

A CPFD (Computational particle fluid dynamics) model of solar fluidized bed receiver of silicon carbide (SiC: average d_p=123 ㎛) particles was established, and the model was verified by comparing the simulation and experimental results to analyze the effect of particle behavior on the performance of the receiver. The relationship between the heat-absorbing performance and the particles behavior in the receiver was analyzed by simulating their behavior near bed surface, which is difficult to access experimentally. The CPFD simulation results showed good agreement with the experimental values on the solids holdup and its standard deviation under experimental condition in bed and freeboard regions. The local solid holdups near the bed surface, where particles primarily absorb solar heat energy and transfer it to the inside of the bed, showed a non-uniform distribution with a relatively low value at the center related with the bubble behavior in the bed. The local solid holdup increased the axial and radial non-uniformity in the freeboard region with the gas velocity, which explains well that the increase in the RSD (Relative standard deviation) of pressure drop across the freeboard region is responsible for the loss of solar energy reflected by the entrained particles in the particle receiver. The simulation results of local gas and particle velocities with gas velocity confirmed that the local particle behavior in the fluidized bed are closely related to the bubble behavior characterized by the properties of the Geldart B particles. The temperature difference of the fluidizing gas passing through the receiver per irradiance (∆T/I_DNI) was highly correlated with the RSD of the pressure drop across the bed surface and the freeboard regions. The CPFD simulation results can be used to improve the performance of the particle receiver through local particle behavior analysis.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.327-339
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• 2022

The purpose of this study is to present the effective smoke control flow rate and mode for securing safety through quantitative risk assessment according to the smoke control flow rate and mode (supply or exhaust) of the platform when a train fire occurs at the subway platform. To this end, a fire outbreak scenario was created using a side platform with a central staircase as a model and fire analysis was performed for each scenario to compare and analyze fire propagation characteristics and ASET, evacuation analysis was performed to predict the number of deaths. In addition, a fire accident rate (F)/number of deaths (N) diagram (F/N diagram) was prepared for each scenario to compare and evaluate the risk according to the smoke control flow rate and mode. In the ASET analysis of harmful factors, carbon monoxide, temperature, and visible distance determined by performance-oriented design methods and standards for firefighting facilities, the effect of visible distance is the largest, In the case where the delay in entering the platform of the fire train was not taken into account, the ASET was analyzed to be about 800 seconds when the air flow rate was 4 × 833 m³/min. The estimated number of deaths varies greatly depending on the location of the vehicle of fire train, In the case of a fire occurring in a vehicle adjacent to the stairs, it is shown that the increase is up to three times that of the vehicle in the lead. In addition, when the smoke control flow rate increases, the number of fatalities decreases, and the reduction rate of the air supply method rather than the exhaust method increases. When the supply flow rate is 4 × 833 m³/min, the expected number of deaths is reduced to 13% compared to the case where ventilation is not performed. As a result of the risk assessment, it is found that the current social risk assessment criteria are satisfied when smoke control is performed, and the number of deaths is the flow rate 4 × 833 m³/min when smoke control is performed at 29.9 people in 10,000 year, It was analyzed that it decreased to 4.36 people.

• Journal of the Korean Chemical Society
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• v.67 no.2
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• pp.81-88
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• 2023

The contribution of hydrophobic residues to the protein folding reaction was studied by using HubWA variant proteins with I and L to V mutation. Folding kinetics of all V variant proteins was observed to be satisfied by a three-state on-pathway mechanism, U ⇌ I ⇌ N, where U, I, and N represent unfolded, intermediate, and native state, respectively. Three-state folding reaction was quantitatively analyzed and the free energy of folding of each elementary reactions and overall folding reaction, ΔG^o_UI, ΔG^o_IN, and ΔG^o_UN, were obtained. From the ratio of free energy difference between the variant protein and HubWA, ΔΔG^o_UI/ΔΔG^o_UN (ΔΔG^o_UI = ΔG^o_UI (variant protein) - ΔG^o_UI (HubWA) and ΔΔG^o_UN = ΔG^o_UN (variant protein) - ΔG^o_UN(HubWA)), the contribution of hydrophobic residues to HubWA folding was analyzed. The residues which are located in the hydrophobic core between α-helix and β-sheet, I3, I13, L15, I30, L43, I61 and L67, showed ΔΔG^o_UI/ΔΔG^o_UN value of ~0.5 when each of these residues was mutated to V, indicating that these residues form relatively solid hydrophobic core in the intermediate state. Residues located at the end of secondary structures and loop, I23, L69 and I36 showed ΔΔG^o_UI/ΔΔG^o_UN value below 0.4 when each of these residues was mutated to V, indicating that the region containing these residues are loosely formed in the intermediate state. V17A, L50V and L56V showed fairly high ΔΔG^o_UI/ΔΔG^o_UN value of ~0.8. Since L50 and L56 are located in the region containing long loop (residue 46 to 62), it is suggested that the high ΔΔG^o_UI/ΔΔG^o_UN value of these residues prevents the formation of aggregate at the early stage of folding reaction.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Trans-
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• v.15
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• pp.25-56
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• 2023

VR is a dynamic image simulation technology with very high information density. Among them, spatial depth, temporality, and realism bring an unprecedented sense of immersion to the experience. However, due to its high information density, the information contained in it is very easy to be manipulated, creating an illusion of objectivity. Users need guidance to help them interpret the high density of dynamic image information. Just like setting up navigation interfaces and interactivity in games, interactivity in virtual reality is a way to interpret virtual content. At present, domestic research on VR content is mainly focused on technology exploration and visual aesthetic experience. However, there is still a lack of research on interactive storytelling design, which is an important part of VR content creation. In order to explore a better interactive storytelling model in virtual reality content, this paper analyzes the interactive storytelling features of the VR animated version of <Wolves in the walls> through the methods of literature review and case study. We find that the following rules can be followed when creating VR content: 1. the VR environment should fully utilize the advantages of free movement for users, and users should not be viewed as mere observers. The user's sense of presence should be fully considered when designing interaction modules. Break down the "fourth wall" to encourage audience interaction in the virtual reality environment, and make the hot media of VR "cool". 2.Provide developer-driven narrative in the early stages of the work so that users are not confused about the ambiguous world situation when they first enter a virtual environment with a high degree of freedom. 1.Unlike some games that guide users through text, you can guide them through a more natural interactive approach that adds natural dialog between the user and story characters (NPC). Also, since gaze guidance is an important part of story progression, you should set up spatial scene user gaze guidance elements within it. For example, you can provide eye-following cues, motion cues, language cues, and more. By analyzing the interactive storytelling features and innovations of the VR animation <Wolves in the walls>, I hope to summarize the main elements of interactive storytelling from its content. Based on this, I hope to explore how to better showcase interactive storytelling in virtual reality content and provide thoughts on future VR content creation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.67-76
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• 2024

In this paper, we present a DIP-MLS testing method that combines digital image processing with a rigid body-based MLS differencing approach to measure mechanical variables and analyze the impact of target location and image resolution. This method assesses the displacement of the target attached to the sample through digital image processing and allocates this displacement to the node displacement of the MLS differencing method, which solely employs nodes to calculate mechanical variables such as stress and strain of the studied object. We propose an effective method to measure the displacement of the target's center of gravity using digital image processing. The calculation of mechanical variables through the MLS differencing method, incorporating image-based target displacement, facilitates easy computation of mechanical variables at arbitrary positions without constraints from meshes or grids. This is achieved by acquiring the accurate displacement history of the test specimen and utilizing the displacement of tracking points with low rigidity. The developed testing method was validated by comparing the measurement results of the sensor with those of the DIP-MLS testing method in a three-point bending test of a rubber beam. Additionally, numerical analysis results simulated only by the MLS differencing method were compared, confirming that the developed method accurately reproduces the actual test and shows good agreement with numerical analysis results before significant deformation. Furthermore, we analyzed the effects of boundary points by applying 46 tracking points, including corner points, to the DIP-MLS testing method. This was compared with using only the internal points of the target, determining the optimal image resolution for this testing method. Through this, we demonstrated that the developed method efficiently addresses the limitations of direct experiments or existing mesh-based simulations. It also suggests that digitalization of the experimental-simulation process is achievable to a considerable extent.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.278-284
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• 2023

Recently, a closed-type plant factory has been receiving attention as a advanced agricultural method. It has diverse advantages such as climate-independence, high productivity and stable year-round production. However, high energy cost caused by environmental control system is considered as a challenges of a closed-type plant factory. In order to reduce the energy cost, investigation about energy load which is directly connected to energy consumption needs to be conducted. In this study, energy load changes of a plant factory have been analytically analyzed according to the environmental changes. The target plant factory was a lettuce growing container farm. Firstly, the impact of photoperiod, set temperature and relative humidity change were examined. Under the climate condition of Daejeon in South Korea, increase of photoperiod and set temperature rose a yearly energy demand of a container farm. However, increase of set relative humidity decreased a yearly energy demand. Secondly, the climate environment effect was compared by investigating the energy demand under 9 different climate conditions. As a result, the difference between maximum and minimum value of the yearly energy demand showed 21.7%. Lastly, sensitivity analysis of each parameter (photoperiod, set temperature and relative humidity) has been suggested under 3 different climate conditions. The ratio of heating and cooling demand was varied depending on the climate, so the effect of each parameter became different.