• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.54-69
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• 2023

This study investigated the distribution of users in urban parks to overcome the limitations of existing research, which made it difficult to determine where data came was collected. It aimed to provide implications for park planning and management based on user distribution using mobile signal data. Five urban parks in Seongdong-gu, Seoul, with various physical characteristics, were selected. Mobile signal data provided by the Seoul Big Data Campus was used to identify the distribution of user inflow through hot spot analysis per park. The relationship between urban context and park influence area was derived. Seoul Forest (P1) and Seongsu Park (P3), which have a high proportion of commercial spaces around the park, showed wider user hotspots compared to Eungbong Park (P2), Dokseodang Park (P4), and Daehyunsan Park (P5), which were located in residential areas. Parks with a significant presence of commercial spaces had a broader influence, while parks with larger sizes and gentle slopes exhibited wider influence areas. This study proposed a novel data-based approach to urban park planning and management based on the inflow distribution of park users. Through this research, valuable insights were derived that could be utilized for urban park planning and management, aiming to enhance the effectiveness and efficiency of park utilization.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.207-207
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• 2022

Eating and cooking quality (ECQ) is one of the most complex quantitative traits in rice. The understanding of genetic regulation of transcript expression levels attributing to phenotypic variation in ECQ traits is limited. We integrated whole-genome resequencing, transcriptome, and phenotypic variation data from 84 Japonica accessions to build a transcriptome-wide association study (TWAS) based regulatory network. All ECQ traits showed a large phenotypic variation and significant phenotypic correlations among the traits. TWAS analysis identified a total of 285 transcripts significantly associated with six ECQ traits. Genome-wide mapping of ECQ-associated transcripts revealed 66,905 quantitative expression traits (eQTLs), including 21,747 local eQTLs, and 45,158 trans-eQTLs, regulating the expression of 43 genes. The starch synthesis-related genes (SSRGs), starch synthase IV-1 (SSIV-1), starch branching enzyme 1 (SBE1), granule-bound starch synthase 2 (GBSS2), and ADP-glucose pyrophosphorylase small subunit 2a (OsAGPS2a) were found to have eQTLs regulating the expression of ECQ associated transcripts. Further, in co-expression analysis, 130 genes produced at least one network with 22 master regulators. In addition, we developed CRISPR/Cas9-edited glbl mutant lines that confirmed the role of alpha-globulin (glbl) in starch synthesis to validate the co-expression analysis. This study provided novel insights into the genetic regulation of ECQ traits, and transcripts associated with these traits were discovered that could be used in further rice breeding.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Information Systems Review
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• v.25 no.1
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• pp.75-91
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• 2023

Thanks to information technologies, sharing economy services offer a new way of consumption. Carsharing appeared as a novel type of service that transformed the conventional way of personal transportation, from owning a vehicle to using an on-demand service. Allowing users to use a vehicle without owning a car, carsharing provides various social benefits such as the reduction of resource allocation inefficiencies and the alleviation of transportation problems. To strengthen such positive aspects of carsharing service, it is essential to understand an individual's service usage pattern and reveal factors that affect users' reuse behavior. This study investigates the factors that have an influence on carsharing reuse of users applying RFMC (Recency, Frequency, Monetary, and Clumpiness) model, the popular model for understanding the reuse likelihood of customers. Using data from a leading carsharing service provider in South Korea, we empirically analyze the effect of RFMC on carsharing reuse behavior. The findings show that recency and monetary values are negatively related to reuse while frequency is positively related to carsharing service reuse. Moreover, the impact of recency and monetary value are more salient whereas the impact of frequency is smaller among users with higher clumpiness. Based on these findings, this study elaborates on theoretical and practical implications.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.77-90
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• 2024

This research aims to investigate methods of leveraging generative artificial intelligence in service sectors where consumer sentiment and experience are paramount, focusing on minimizing hallucination phenomena during usage and developing strategic services tailored to consumer sentiment and experiences. To this end, the study examined both mechanical approaches and user-generated prompts, experimenting with factors such as business item definition, provision of persona characteristics, examples and context-specific imperative verbs, and the specification of output formats and tone concepts. The research explores how generative AI can contribute to enhancing the accuracy of personalized content and user satisfaction. Moreover, these approaches play a crucial role in addressing issues related to hallucination phenomena that may arise when applying generative AI in real services, contributing to consumer service innovation through generative AI. The findings demonstrate the significant role generative AI can play in richly interpreting consumer sentiment and experiences, broadening the potential for application across various industry sectors and suggesting new directions for consumer sentiment and experience strategies beyond technological advancements. However, as this research is based on the relatively novel field of generative AI technology, there are many areas where it falls short. Future studies need to explore the generalizability of research factors and the conditional effects in more diverse industrial settings. Additionally, with the rapid advancement of AI technology, continuous research into new forms of hallucination symptoms and the development of new strategies to address them will be necessary.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.114-121
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• 2023

Selective cyclooxygenase (COX)-2 inhibition is a novel strategy to reduce the risk of gastrointestinal side effects caused by conventional nonsteroidal anti-inflammatory drugs. However, some selective COX-2 inhibitors have become apparent to increase the risk of severe cardiovascular disease. The aim of this study was to examine the anti-inflammatory effect of rosemary extract (RE) and confirm the safety of cardiovascular side effects. Inhibition of COX enzyme activity was assessed, and the levels of COX-2 and prostaglandin E₂ (PGE₂) and COX-1 and thromboxane B₂ (TXB₂) were evaluated in lipopolysaccharide (LPS)-induced RAW 264.7 cells. The 40% RE group showed increased COX-2 inhibition activity in a dose-dependent manner, whereas the 50% RE group only exhibited at 100 ㎍/mL. In a cell-based study, COX-2 mRNA expression was similar in both RE groups and PGE₂ levels tended to decrease in the 40% RE group compared to the LPS group in the LPS pretreatment condition. In the LPS posttreatment condition, the COX-2 mRNA expression decreased in the 40% RE group, and PGE₂ levels were increased in the 40 and 50% RE groups. In both conditions, there was no significant difference in COX-1 and TXB₂ levels. In conclusion, 40 and 50% RE showed significant COX-2 inhibition, similar to the positive control group. It was confirmed that the inhibition of the COX-2 expression, but the effect did not affect the balance between prostacyclin and TXB₂. These results indicate that rosemary showed COX-2 inhibition activity with a low risk of cardiovascular diseases.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2174-2181
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• 2024

In this work, Sr_0.5Zr₂(PO₄)₃-SmPO₄ dual-phase ceramics were prepared via in-situ synthesis process, which is a potential novel nuclear waste form for immobilizing the fission product ⁹⁰Sr and the trivalent actinide radionuclides in high-level waste (HLW). And the preparation technology, microstructure and chemical durability of Sr_0.5Zr₂(PO₄)₃-SmPO₄ dual-phase ceramics were systematically investigated. It was confirmed that the optimum microwave-sintering temperature (1050 ℃) and heat preservation time (1.5 h) is estimated by Archimedes method. Besides, the as-prepared samples that were consisted of strontium zirconium phosphate (SrZP) and monazite showed the remarkable densification, in which the two crystalline phases were intermixed well with each other. Meanwhile, the formation and evolution of microstructure was also consistent with the variational rule of Sr_0.5Zr₂(PO₄)₃/SmPO₄, indicating that there was not mutual reaction during the in-situ synthesis process. The PCT and MCC-1 experimental results demonstrated that the elemental normalized leaching rates of tested samples are all at a low level (LR_Sr ~10^-4 g·m^-2·d^-1, LR_Zr ~10^-8-10^-6 g·m^-2·d^-1, LR_Sm ~10^-7-10^-5 g·m^-2·d^-1 and LR_P ~10^-4 g·m^-2·d^-1). It is indicated that Sr_0.5Zr₂(PO₄)₃-SmPO₄ dual-phase ceramics possesses excellent chemical durability for HLW disposal.

• Journal of Life Science
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• v.25 no.9
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• pp.1027-1035
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• 2015

A strain GP32 which produces a highly viscous extracellular polysaccharide was conducted with soil samples and identified as Pseudomonas species. The culture flask conditions for the production of extracellular polysaccharide by Pseudomonas sp. GP32 were investigated. The most suitable carbon and nitrogen source for extracellular polysaccharide production were galactose and (NH₄)₂SO₄. The optimum carbon/nitrogen ratio for the production of extracellular polysaccharide was around 50. The optimum pH and temperature for extracellular polysaccharide production was 7.5 and 32℃, respectively. In batch fermentation using a jar fermentor, the highest extracellular polysaccharide content (15.7 g/l) was obtained after 70 hr of cultivation. The extracellular polysaccharide produced by Pseudomonas sp. GP32 (designated Biopol32) was purified by ethanol precipitation, cetylpyridinium chloride (CPC) precipitation, and gel permeation chromatography. Biopol32, which has an estimated molecular weight of over 3×10⁷ datons, is a novel polysaccharide derived from sugar components consisting of galactose, glucose, gulcouronic acid and galactouronic acid in an approximate molar ratio of 1.85 : 3.24 : 1.00 : 1.42. The solution of Biopol32 showed non-Newtonian characteristics. The viscosity of Biopol32 exhibited appeared to be higher at all concentration compared to that of zooglan from Zoogloea ramigera. An analysis of the flocculating efficiency of Biopol32 in industry wastewater (food, textile, and paper wastewater) revealed chemical oxygen demand (COD) reduction rates 58.4-67.3% and suspended solid (SS) removal rates 82.6-91.3%. Based on these results, Biopol32 is a possible candidate for industrial applications such as wastewater treatment.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.83-98
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• 2015

Many TV viewers use mainly portal sites in order to retrieve information related to broadcast while watching TV. However retrieving information that people wanted needs a lot of time to retrieve the information because current internet presents too much information which is not required. Consequentially, this process can't satisfy users who want to consume information immediately. Interactive video is being actively investigated to solve this problem. An interactive video provides clickable objects, areas or hotspots to interact with users. When users click object on the interactive video, they can see additional information, related to video, instantly. The following shows the three basic procedures to make an interactive video using interactive video authoring tool: (1) Create an augmented object; (2) Set an object's area and time to be displayed on the video; (3) Set an interactive action which is related to pages or hyperlink; However users who use existing authoring tools such as Popcorn Maker and Zentrick spend a lot of time in step (2). If users use wireWAX then they can save sufficient time to set object's location and time to be displayed because wireWAX uses vision based annotation method. But they need to wait for time to detect and track object. Therefore, it is required to reduce the process time in step (2) using benefits of manual annotation method and vision-based annotation method effectively. This paper proposes a novel annotation method allows annotator to easily annotate based on face area. For proposing new annotation method, this paper presents two steps: pre-processing step and annotation step. The pre-processing is necessary because system detects shots for users who want to find contents of video easily. Pre-processing step is as follow: 1) Extract shots using color histogram based shot boundary detection method from frames of video; 2) Make shot clusters using similarities of shots and aligns as shot sequences; and 3) Detect and track faces from all shots of shot sequence metadata and save into the shot sequence metadata with each shot. After pre-processing, user can annotates object as follow: 1) Annotator selects a shot sequence, and then selects keyframe of shot in the shot sequence; 2) Annotator annotates objects on the relative position of the actor's face on the selected keyframe. Then same objects will be annotated automatically until the end of shot sequence which has detected face area; and 3) User assigns additional information to the annotated object. In addition, this paper designs the feedback model in order to compensate the defects which are wrong aligned shots, wrong detected faces problem and inaccurate location problem might occur after object annotation. Furthermore, users can use interpolation method to interpolate position of objects which is deleted by feedback. After feedback user can save annotated object data to the interactive object metadata. Finally, this paper shows interactive video authoring system implemented for verifying performance of proposed annotation method which uses presented models. In the experiment presents analysis of object annotation time, and user evaluation. First, result of object annotation average time shows our proposed tool is 2 times faster than existing authoring tools for object annotation. Sometimes, annotation time of proposed tool took longer than existing authoring tools, because wrong shots are detected in the pre-processing. The usefulness and convenience of the system were measured through the user evaluation which was aimed at users who have experienced in interactive video authoring system. Recruited 19 experts evaluates of 11 questions which is out of CSUQ(Computer System Usability Questionnaire). CSUQ is designed by IBM for evaluating system. Through the user evaluation, showed that proposed tool is useful for authoring interactive video than about 10% of the other interactive video authoring systems.