• Korean Journal of Plant Resources
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• v.36 no.2
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• pp.107-121
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• 2023

This study analyzed the polyphenol, flavonoid contents, antioxidant activity, anti-aging activity and phenol component contents of Saccharina japonica (SJ), Costaria costata (CC) extracts with hot water, 95% methanol, 95% prethanol for investigating possible utilization of SJ and CC extracts. The result revealed that the SJ and CC methanol extracts showed the highest polyphenol and flavonoid contents, 4.63 mg TAN/g, and 4.19 mg QUE/g respectively. Also, the SJ and CC methanol extracts showed higher antioxidant activity than prethanol and hot water extracts, whereas the ABTS radical scavenging activities were the highest in prethanol extracts (IC₅₀ = 15.4, 10.3 ㎍/µL). In anti-aging activity for evaluating the anti-wrinkle activity and skin whitening activity, the CC methanol extracts had high collagenase inhibitory activity (88.3%), and the SJ prethanol extracts showed higher elastase inhibitory activity (19.0%) compared to other extracts. Then the tyrosinase inhibitory activity was significantly higher in the SJ and CC methanol extracts (41.8, 30.3%, respectively), whereas prethanol extracts were the lowest. To identify the phenol component contents of SJ and CC extracts, 4-hydroxybenzoic acid, naringenin, naringin and nicotinic acid were measured using LC-MS/MS. As a result, the phenol contents were the highest in SJ methanol extract (4-hydroxybenzoic acid), SJ and CC prethanol extract (naringin and naringenin) and CC prethanol extract (nicotinic acid). Lastly, the antioxidant activity of SJ and CC showed high correlations with polyphenol and flavonoid contents (R = -0.946~0.883). These results suggest that prethanol or methanol extracts of SJ and CC have higher antioxidant activities, anti-aging activity and the potential to be used as material for health functional food and cosmetics.

• Research in Plant Disease
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• v.29 no.3
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• pp.268-275
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• 2023

This study was conducted to confirm the utilization of Pleurospermum camtschaticum root extract as an organic agricultural material. Antioxidant activity of P. camtschaticum root extract, closely related to antibacterial activity, increased in a dose-dependent manner. In mycelial growth inhibitory activity, 100% P. camtschaticum root extract supressed over 70% for Colletotrichum coccodes and over 68% for Colletotrichum dematium. In the pepper fruit anthracnose development test, the size of the lesion decreased in a dose-dependent manner, which showed the same tendency as the previous results in inhibitory activity on mycelial growth. In the pepper seed germination and red pepper growth promotion test of P. camtschaticum root extract, oposite results was confirmed. The lower the concentration, the more the seed germination and growth promotion effects were shown. The phenol content of pepper leaves was also measured after pepper growth promotion test have been completed. The phenol content related to antibacterial activity increased in all treated groups compared to the untreated group. Therefore, the results of this study showed the possibility of development as an organic material.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.1
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• pp.89-103
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• 2023

The purpose of this study was to measure bone age using an artificial intelligence program based on the Greulich-Pyle (GP) method to find out the bone age corresponding to each stage of cervical vertebral maturation (CVM) and the middle phalanx of the third finger (MP3). This study was conducted on 3,118 patients who visited pediatric dentistry at Kyung Hee University Dental Hospital and Pusan National University Dental Hospital from 2013 to 2021. The CVM stage was divided into 5 stages according to the classification by Baccetti, and the MP3 stage was divided into 5 stages according to the methods of Hägg and Taranger. Based on the GP method, bone age was evaluated using an artificial intelligence program. The pubertal growth spurt in the CVM stage was CVM II and III. The mean bone age in CVM II was 11.00 ± 1.81 years for males and 10.00 ± 1.49 years for females, and in CVM III, 13.00 ± 1.46 years for males and 12.00 ± 1.44 years for females (p < 0.0001). The pubertal growth spurt in the MP3 stage was MP3 - G stage. The bone age at the MP3 - G stage was 13.14 ± 1.07 years for males and 11.40 ± 1.09 years for females (p < 0.0001). Bone age evaluation using artificial intelligence is worth using in clinical practice, and it is expected that a faster and more accurate diagnosis will be possible.

• (The) Research of the performance art and culture
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• no.40
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• pp.193-222
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• 2020

In this study, the development of traditional contents is to be enabled to succeed the values of the heritage on the song sang during dry-field farming of Bongpyeong Memil-dorikkaejil-sori. In addition, the identity on the heritage of songs sang during farming were diagnosed, and their value in context with the history and the value as the community for succession are emphasized as the value of cultural asset to expand the discussion up to the level of traditional cultural industry works. In the Bongpyeong Memil-dorikkaejil-sori, the intrinsic artistic value, the excellence of value as the educational experience, factor for overcoming the extinction of farming songs, and the promotion direction of the storytelling on buckwheat were provided. This is breaking from the formalization and being old-fashioned on the Bongpyeong Memil-dorikkaejil-sori to focus on the symbolization of the agricultural heritage in the modern context, habituating and spreading the gene of slash-and-burn field (hwajeon or budaeki). In terms of methodology on awareness, historicity or creativity, alternative method on the folk songs in labor was provided by having critical mind on the Bongpyeong Memil-dorikkaejil-sori and buckwheat songs. By reviewing the field contextualization of designating the intangible cultural asset, suggestions were made on activating the succession, and even the method of symbolic registration on the heritage of buckwheat farming was mentioned. Heritage on agricultural culture that can represent Pyeongchang and Gangwon must be discovered to be made into a brand. In addition, the uniqueness in the Madang 'Song Madaengi Traditional Music' must be found to apply as the brand on the point in which the people around the world can have consensus for utilization. As the farming song, rediscovery of the Bongpyeong Memil-dorikkaejil-sori is required to create the sustainable status as the multi-purpose cultural contents and provide the network of professionals for activating the folk songs to enable the opportunity of qualitative substantiality and spread instead of quantitative growth. In addition, festivals for each region, especially the festival for Pyeongchang area must be utilized centrally on the development of farming songs to organize the storytelling actively.

• Journal of Practical Agriculture & Fisheries Research
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• v.4 no.1
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• pp.119-127
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• 2002

This study was conducted to develop the heat exchanger by utilizing the heat energy of underground water(15℃), which might be used for cooling and heating system of the agricultural facilities. We developed the heat exchanger, parallel type plat fin tube made of Aluminum(Al 6063), which was named Aloo-Heat(No. of The registration design : 0247164, by Korean Intellectual property Office). The fin of exchanger was design of the granulated surface for minimizing fouling factor and dew forms, and also placed parallel to the tube in order to minimized the resistance of flows. 1. Aloo-heat was designed to have 0.03m for inside diameter, 0.036m for outside diameter of tube, 0.0012m for thickness of fin and 0.032m for length of plat fin. 2. t was also designed to have 1.5248m²/m for outside area of heat transfer, 0.0942m²/m for inside area contacting hot liquid, and the ratio (Ra) was 16.1869. 3. Efficiency of the fin was 93 percentage when fin length was 0.032m, and the fin thickness satisfied equation $\frac{h{\rho}}{k}$< 0.2 when it was 0.0012m. 4. According to the performance test of Aloo-heat, as the temperature and rate increased, the heating value also increased, heating value was 504kJ/h·m and 6,048kJ/h·m when it was 60℃, 10 𝑙/min and 80℃, 40 𝑙/min respectively. 5. The test of heating value was confident, because correlation value(R²) was 0.9898 for the temperature and 0.9721 for flow rate of hot liquid, respectively.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Journal of Practical Agriculture & Fisheries Research
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• v.25 no.1
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• pp.5-13
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• 2023

This study was conducted to identify items that should be considered in order to increase user satisfaction in the Jayeonmadang project by analyzing the importance and satisfaction targeting Gochang Jayeonmadang users. As a result of analysis on the importance and satisfaction of Gochang Jayeonmadang users focusing on 20 items in 6 fields, Overall, it was analyzed that they were not satisfied as they were important. In order to increase user satisfaction of Gochang Jayeonmadang, maintenance such as 'cleanliness and hygiene', 'water quality', 'vegetation growth', and 'facility management' should be carefully reflected from the planning and design stage, and careful attention should be paid even after the project. In addition, emphasis should be placed on enhancing the user convenience, such as 'accessibility', 'space layout and utilization efficiency', and 'convenience of route'. And, when promoting the Jayeonmadang project, the purpose of the project should be actively promoted to local residents to raise the residents' awareness of the importance of biodiversity in the city.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.231-238
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• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.

• 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.