• Conservation Science in Museum
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• v.29
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• pp.1-32
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• 2023

The Paintings of a 60^th Wedding Anniversary Ceremony Created by an Unknown Painter (Deoksu 6375), housed by the National Museum of Korea, is a five-panel painting book depicting scenes from a wedding ceremony. Hoehonrye is a type of repeated wedding ceremony to commemorate a couple's 60th wedding anniversary with congratulations from the community. The paintings of the book record five scenes from the wedding: jeoninrye, a ceremony where the groom brings a wooden wild goose to the bride's house; gyoberye, the groom and the bride bowing to each other; heosurye, pouring liquor to toast to the couple's longevity; jeopbin, offering tea to guests; and a banquet to celebrates the couple's 60th wedding anniversary. The book describes figures, buildings and a variety of items in detail with delicate brushstrokes. The techniques were examined using microscopy, infrared, and X-ray irradiation and hyperspectral imaging analysis. The invisible parts were examined to identify the rough sketch and distinguish pigments and dyes used for each color. The components of the pigments were determined by X-ray fluorescence analysis, while the dyes were identified by UV-vis spectrometry. Microscope observation revealed that the fabric used for the paintings was raw silk thread with almost no fiber twist, and plain silk fabric. Hyperspectral imaging analysis, X-ray fluorescence analysis, and UV-vis spectrometry confirmed that the white pigment was white lead and the black was chinese ink. The red pigments were using red clay, cinnabar, and a mixture of cinnabar and minium. Brown was made using red clay and organic dyes, and yellow using gamboge. Green was identified as indigo, malachite, chrome green, barium sulfide, and blue as azurite, smalt, and indigo. The purple dye was estimated as a mixture of indigo and cochineal, and gold parts were used gold powder. Hyperspectral images were distinguished parts damaged and conservation treatment area.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Journal of Life Science
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• v.32 no.3
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• pp.189-195
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• 2022

Kinesin-2 comprises two subfamilies of the heterotrimeric or homodimeric motors found in mammalian cells. Heterotrimeric kinesin-2 consists of kinesin superfamily proteins (KIFs) 3A and 3B and kinesin-associated protein 3 (KAP3), which is a molecular motor protein that moves along microtubules. It plays diverse roles in cargo transport, including anterograde trafficking in cilia, and interacts with many different cargoes and proteins, but their binding proteins have not yet been fully identified. In this study, the yeast two-hybrid assay was used to identify the proteins that interact with the cargo-binding domain (CBD) of KIF3A, and an interaction between KIF3A and brain expressed X-linked 2 (Bex2) was found. Bex2 bound to the CBD-containing C-terminal tail region of KIF3A but did not interact with the same region of KIF3B or KIF5A (a motor protein of kinesin-1). KIF3A interacted with another isoform, Bex1, but did not interact with Bex3. In addition, glutathione S-transferase (GST) pull-downs showed that KIF3A specifically interacts with GST-Bex1 and GST-Bex2 but not with GST alone. When co-expressed in HEK-293T cells, Bex2 co-localized with KIF3A and co-immunoprecipitated with KIF3A and KIF3B but not KIF5B. In combination, these results suggest that Bex2 is capable of binding to heterotrimeric kinesin-2 and may serve as an adaptor protein that links heterotrimeric kinesin-2 with cargo.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.1-9
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• 2022

An estuary is an area where a freshwater river or stream meets the ocean. Even before the importance of the value of estuaries was recognized, the estuary was lost because of large-scale conversion by draining, filling, damming, and dredging. In South Korea, 643 estuaries are located, and the total area is 3,248,300 ha, accounting for 32.5% of the total area of South Korea. Over 35% of Korean estuaries are closed estuaries which are only temporally connected with the sea, either permanently or periodically. Since 2008, in order to preserve the estuary ecosystem and solve major issues in the estuary by accumulating knowledge about the estuarine ecosystem, the Ministry of Environment of Republic of Korea has been conducting the "Estuarine Ecosystem Monitoring and Assessment Project". At 668 sites of 325 estuaries, epilithic diatom, benthic macroinvertebrate, fish, and vegetation are investigated, and the habitat condition of each site is evaluated using the newly developed biotic index. More than 100 researchers annually record 2,097 species of estuaries according to the standardized survey guidelines over the past 14 years and provide strictly managed data necessary for establishing estuaries conservation policies. As a result of bibliometric analysis of 1,195 research articles related to the monitoring and assessment of the estuarine ecosystem, research on pollutants such as heavy metals and sediment control have recently been conducted. "Estuarine Ecosystem Monitoring and Assessment Project" is an ecological monitoring type of long-term mandated monitoring that is usually focused on identifying trends. Although it is difficult to identify the mechanism influencing a change in an ecosystem through long-term mandated monitoring, providing empirical data for supporting evidence-based policy, decision-making, and the management of ecosystems. In order to increase the efficiency of the project, research to investigate the relationship between sediments and pollutants and organisms can be conducted at specific estuaries or sites to compensate for the shortcomings of mandatory monitoring.

• 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.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.113-126
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• 2022

The tectonic history of the Chukchi Abyssal Plain in the Amerasia Basin, Arctic Ocean, has not been fully explored due to the harsh conditions of sea ice preventing detailed observation. Existing models of the tectonic history of the region provide contrasting interpretation of the timing of formation of the crust (Mesozoic to Cenozoic), crust type (from hyper-extended continental crust to oceanic crust), and formation process (from parallel/fan-shaped rifting to transformation faulting). To help determine the age of the oceanic crust, the geothermal gradient was measured at three stations in the south of abyssal plain at depth of 2,160-2,250 m below sea level. Heat flow measurement stations were located perpendicular to the spreading axis over a 40 km-long transect. In-situ thermal conductivity measurement, corrected by the laboratory test, gave observed marine heat flows of 55 to 61 mW/m². All measurements were taken during Arctic expeditions in 2018 (ARA09C expedition) and 2021 (ARA12C expedition) by the Korean ice-breaking research vessel (IBRV) Araon. Given the assumption of oceanic crust, the results correspond to formation in the Late Cretaceous (Mesozoic). The inferred age supports the hypothesis of formation activated by the opening of the Makarov Basin during the Late Mesozoic-Cenozoic. This would make it contemporaneous with rifting of the Chukchi Border Land immediately east of the abyssal plain. The heat flow data indicate the base of the gas hydrate stability zone is located 332-367 m below the seafloor, this will help to identify the gas hydrate-related bottom simulating reflector in the future seismic survey, as already identified on the Chukchi Plateau. Further geophysical surveys, including heat flow measurements, are required to increase our understanding of the formation process and thermal mantle structure of the abyssal plain.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of the Korean Orthopaedic Association
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• v.54 no.4
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• pp.309-316
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• 2019

Purpose: This study examined the residential environment and accessibility of rehabilitation for cerebral palsy (CP) to identify the problems with residential laws pertaining to the disabled and provide basic data on the health legislation for the rights of the disabled. Materials and Methods: The literature was searched using three keywords: residence, rehabilitation, and accessibility. Two items were selected: residential environment and rehabilitation accessibility. The questionnaire included 51 items; 24 were scored using a Likert scale and 27 were in the form of multiple-choice questions. Results: This study included 100 subjects, of which 93 lived at home and seven lived in a facility. Of these 93 subjects, 65% were living in apartments, usually two or more floors above ground, and 40% of them were living without elevators. According to the Gross Motor Function Classification System, subjects with I to III belonged to the ambulatory group and IV, V were in the non-ambulatory group. Subjects from both groups who lived at home found it most difficult to visit the rehabilitation center by themselves. In contrast, among those who lived at the facility, the ambulatory group found it most difficult to leave the facility alone, while the non-ambulatory group found it most difficult to use the toilet alone. Moreover, 83% of respondents thought that rehabilitation was necessary for CP. On the other hand, 33% are receiving rehabilitation services. Rehabilitation was performed for an average of 3.6 sessions per week, 39 minutes per session. Conclusion: There is no law that ensures secure and convenient access of CP to higher levels. Laws on access routes to enter rooms are insufficient. The disabled people's law and the disabled person's health law will be implemented in December 2017. It is necessary to enact laws that actually reflect the difficulties of people with disabilities. Based on the results of this study, an investigation of the housing and rehabilitation of patients with CP through a large-scale questionnaire will necessary.

• Journal of the Korean Orthopaedic Association
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• v.54 no.1
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• pp.59-66
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• 2019

Purpose: Several radiologic reference lines have been used to evaluate individuals with a clubfoot but there is no consensus as to which is most reliable. The aim of this study was to identify which radiologic parameters have relevance to the predictability of additional surgery after Ponseti casting on clubfoot and the effect of clubfoot treatments that contain Ponseti casting and additional surgery. Materials and Methods: A total of 102 clubfeet (65 patients, 37 bilateral) were reviewed from 2005 to 2013. The patients were divided into two groups (Group A, those for whom the result of the Ponseti method was successful and did not require additional surgery; and Group B, those for whom the result of the Ponseti method was unsuccessful and required additional surgery), and the following parameters were measured on the plain radiographs: i) talo-calcaneal angle on the anteroposterior and lateral view, ii) talo-1st metatarsal angle on the anteroposterior view, and iii) Tibio-calcaneal angle on the lateral view with the ankle full-dorsiflexion state. Each radiograph was reviewed on two separate occasions by one orthopedic doctor to characterize the intra-observer reliability, and the averages were analyzed. Next, 20 cases were chosen using a random number table, and two orthopedic doctors measured the angle separately to characterize the interobserver reliability. Results: Groups A and B included 73 clubfeet (71.6%) and 29 clubfeet (28.4%), respectively. The initial talo-calcaneal angle and tibiocalcaneal angle in the lateral view were significantly different among the groups. In addition, inter- and intra-observer biases were not detected. The talo-1st metatarsal angle on the anteroposterior view and tibio-calcaneal angle on the lateral view were significantly different after treatment in both groups. Conclusion: Congenital clubfeet treated with the Ponseti method showed successful results in more than 70% of patients. The initial talocalcaneal angle and tibio-calcaneal angle on the lateral view were the radiologic parameters that could predict the need for additional surgical treatments. The talo-1st metatarsal angle on the anteroposterior view and tibio-calcaneal angle on the lateral view could effectively evaluate the changes in clubfoot after treatment.

• Journal of the Korean Orthopaedic Association
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• v.54 no.5
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• pp.427-434
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• 2019

Purpose: This study evaluated the long term clinical and radiographic results and the survival rates of unicompartmental knee arthroplasty (UKA). In addition, the factors affecting the survival of the procedure were analyzed and the survival curve was compared according to the affecting factors. Materials and Methods: Ninety-nine cases of UKA performed between December 1982 and January 1996 were involved: 10 cases with Modular II, 44 cases with Microloc, and 45 cases with Allegretto prostheses. The mean follow-up period was 16.5 years. Clinically, the hospital for special surgery (HSS) scoring system and the range of motion (ROM) were evaluated. Radiographically, the femorotibial angle (FTA) was measured. The survival rate was analyzed using the Kaplan-Meier method. Cox regression analysis was used to identify the factors affecting the survival according to age, sex, body mass index, preoperative diagnosis, and type of implant. The Kaplan-Meier survival curves were compared according to the factors affecting the survival of UKA. Results: The overall average HSS score and ROM was 57.7 and 134.3° preoperatively, 92.7 and 138.4° at 1 year postoperatively, and 79.1 and 138.4° at the last follow-up (p<0.001, respectively). The overall average FTA was varus 0.8° preoperatively, valgus 4.1° at postoperative 2 weeks, and valgus 3.0° at the last follow-up. The overall 5-, 10-, 15- and 20-year survival rates were 91.8%, 82.9%, 71.0%, and 67.0%, respectively. The factors affecting the survival were the age and type of implant. The risk of the failure decreased with age (hazard ratio=0.933). The Microloc group was more hazardous than the other prostheses (hazard ratio=0.202, 0.430, respectively). The survival curve in the patients below 60 years of age was significantly lower than those of the patients over 60 years of age (p=0.003); the survival curve of the Microloc group was lower compared to the Modular II and Allegretto groups (p=0.025). Conclusion: The long-term clinical and radiographic results and survival of UKA using old fixed bearing prostheses were satisfactory. The selection of appropriate patient and prosthesis will be important for the long term survival of the UKA procedure.