• Korean Journal of Radiology
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• v.22 no.4
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• pp.559-567
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• 2021

Objective: To evaluate the impact of multiparametric magnetic resonance imaging (mpMRI) before confirmatory prostate biopsy in patients under active surveillance (AS). Materials and Methods: This retrospective study included 170 patients with Gleason grade 6 prostate cancer initially enrolled in an AS program between 2011 and 2019. Prostate mpMRI was performed using a 1.5 tesla (T) magnetic resonance imaging system with a 16-channel phased-array body coil. The protocol included T1-weighted, T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging sequences. Uroradiology reports generated by a specialist were based on prostate imaging-reporting and data system (PI-RADS) version 2. Univariate and multivariate analyses were performed based on regression models. Results: The reclassification rate at confirmatory biopsy was higher in patients with suspicious lesions on mpMRI (PI-RADS score ≥ 3) (n = 47) than in patients with non-suspicious mpMRIs (n = 61) and who did not undergo mpMRIs (n = 62) (66%, 26.2%, and 24.2%, respectively; p < 0.001). On multivariate analysis, presence of a suspicious mpMRI finding (PI-RADS score ≥ 3) was associated (adjusted odds ratio: 4.72) with the risk of reclassification at confirmatory biopsy after adjusting for the main variables (age, prostate-specific antigen density, number of positive cores, number of previous biopsies, and clinical stage). Presence of a suspicious mpMRI finding (adjusted hazard ratio: 2.62) was also associated with the risk of progression to active treatment during the follow-up. Conclusion: Inclusion of mpMRI before the confirmatory biopsy is useful to stratify the risk of reclassification during the biopsy as well as to evaluate the risk of progression to active treatment during follow-up.

• Journal of The Korean Association For Science Education
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• v.27 no.9
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• pp.930-943
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• 2007

The purpose of this study was to investigate if students may actually experience scientific reasoning based on an epistemology of authentic science during authentic open inquiry. The samples were 86 10th graders in a science-high school in Seoul. The experimental group practiced authentic open inquiry and the control group practiced traditional school science inquiry in five weeks. Then, the questions students asked while performing inquiry tasks were analyzed. The frequency of the questions asked by students was almost same between two groups, however, the types of questions were different. The frequency of thinking questions in experimental group was higher than the control, and the difference was statistically significant (P<.01). Particularly, the frequency of expansive thinking questions and anomaly detection questions was much higher in experimental than the control group. Judging from the result, with the students from the experimental group asking questions reflecting on the epistemology of authentic science such as scientific methods, anomalous data, and uncertainty about reasoning, students may understand authentic science features during the activities of open authentic inquiry. The result from comparing questions according to the inquiry subject showed that more openness caused the higher frequency of anomaly detection questions and strategy questions, but that inductive thinking questions and analogical thinking questions were connected to inquiry subject rather than the openness of the inquiry.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.2
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• pp.101-115
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• 2024

The ocean heatwave is emerging as a major issue due to global warming, posing a direct threat to marine ecosystems and humanity through decreased food resources and reduced carbon absorption capacity of the oceans. Consequently, the prediction of ocean heatwaves in the vicinity of the Korean Peninsula is becoming increasingly important for marine environmental monitoring and management. In this study, an LSTM model was developed to improve the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system of the Korean Peninsula Ocean Prediction System. Based on the results of ocean heatwave predictions for the Korean Peninsula conducted in 2023, as well as those generated by the LSTM model, the performance of heatwave predictions in the East Sea, Yellow Sea, and South Sea areas surrounding the Korean Peninsula was evaluated. The LSTM model developed in this study significantly improved the prediction performance of sea surface temperatures during periods of temperature increase in all three regions. However, its effectiveness in improving prediction performance during periods of temperature decrease or before temperature rise initiation was limited. This demonstrates the potential of the LSTM model to address the underestimated prediction of ocean heatwaves caused by the coarse vertical grid system during periods of enhanced stratification. It is anticipated that the utility of data-driven artificial intelligence models will expand in the future to improve the prediction performance of dynamical models or even replace them.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Korean Journal of Environment and Ecology
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• v.38 no.1
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• pp.48-54
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• 2024

This study conducted a survey from April 2021 to December 2022 to investigate habitat factors affecting bird diversity in the region between Cheonwangbong Peak and Aghwibong in Baekdudaegan protected area, South Korea. Since the region has a spatial scale of 736.4 km² and is an area where a wide variety of habitats are mixed, we selected 20 survey areas of 3 km x 3 km by analysis of habitat homogeneity. As a result of analyzing the relationship between habitat environment and bird diversity in the survey area, it was found that the diversity of bird communities was directly or indirectly related to the diversity of terrestrial insects, slope, average habitat area, mean size of patches, elevation, and forest type, and distance from agricultural land. The slope of habitat, forest type, and distance from agricultural land affect the occurrence of food sources directly and indirectly, and the average area of habitats and forest type is closely related to the structural diversity of habitats. Therefore, it is determined that the diversity of bird communities is affected by the amount of food generated within the habitat and the diversity of habitats. It is determined that the relationship between bird communities and habitat environments in this surveyed region can be basic ecological data for establishing forest management measures to promote the diversity of bird communities.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.192-199
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• 2024

Wave overtopping is a significant natural hazard that occurs in coastal areas, primarily driven by high waves, particularly those generated during typhoons, which can cause coastal flooding. The development of residential and commercial areas along the coast, driven by increasing social and economic demands, has led to a concentration of people and assets in these vulnerable areas. This, coupled with long-term sea level rise and an increase in typhoon frequency, has heightened the risk of coastal hazards. Traditionally, the evaluation of wave overtopping volumes has relied on directly measuring the collected volume of water that exceeds the crest height of structures through hydraulic model experiments. These experiments are averaged over a specific measurement period. However, in this study, we propose a new method for estimating individual wave overtopping volumes. We utilize the temporal variation of wave overtopping heights to develop an observation system that can quantitatively assess wave overtopping volumes in actual coastal areas. To test our method, we conducted hydraulic model experiments on rubble mound breakwaters, which are commonly installed along the Korean coast. We introduce wave overtopping discharge coefficients, assuming that the inundation velocity from the structure's crest is the long-wave velocity. We then predict overtopping volumes based on wave overtopping heights and compare and review the results with experimental data. The findings of our study confirm the feasibility of estimating wave overtopping volumes by applying the overtopping discharge coefficients derived in this study to wave overtopping heights.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.243-256
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• 2024

Objective: We aimed to investigate whether 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[¹⁸F]FDG PET/CT for endoscopy-detected ampullary tumors 5-87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13-36.18; P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80-13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41-19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00-14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16-21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874-0.956] vs. 0.815 [0.732-0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816-0.967) in candidates for endoscopic papillectomy. Conclusion: Adding 2-[¹⁸F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.803-811
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• 2024

Nuclear accidents such as Fukushima Daiichi have highlighted the potential of passive safety systems to replace or complement active safety systems as part of the overall prevention and/or mitigation strategies. In addition, passive systems are key features of Small Modular Reactors (SMRs), for which they are becoming almost unavoidable and are part of the basic design of many reactors available in today's nuclear market. Nevertheless, their potential to significantly increase the safety of nuclear power plants still needs to be strengthened, in particular the ability of computer codes to determine their performance and reliability in industrial applications and support the safety demonstration. The PASTELS project (September 2020-February 2024), funded by the European Commission "Euratom H2020" programme, is devoted to the study of passive systems relying on natural circulation. The project focuses on two types, namely the SAfety COndenser (SACO) for the evacuation of the core residual power and the Containment Wall Condenser (CWC) for the reduction of heat and pressure in the containment vessel in case of accident. A specific design for each of these systems is being investigated in the project. Firstly, a straight vertical pool type of SACO has been implemented on the Framatome's PKL loop at Erlangen. It represents a tube bundle type heat exchanger that transfers heat from the secondary circuit to the water pool in which it is immersed by condensing the vapour generated in the steam generator. Secondly, the project relies on the CWC installed on the PASI test loop at LUT University in Finland. This facility reproduces the thermal-hydraulic behaviour of a Passive Containment Cooling System (PCCS) mainly composed of a CWC, a heat exchanger in the containment vessel connected to a water tank at atmospheric pressure outside the vessel which represents the ultimate heat sink. Several activities are carried out within the framework of the project. Different tests are conducted on these integral test facilities to produce new and relevant experimental data allowing to better characterize the physical behaviours and the performances of these systems for various thermo-hydraulic conditions. These test programmes are simulated by different codes acting at different scales, mainly system and CFD codes. New "system/CFD" coupling approaches are also considered to evaluate their potential to benefit both from the accuracy of CFD in regions where local 3D effects are dominant and system codes whose computational speed, robustness and general level of physical validation are particularly appreciated in industrial studies. In parallel, the project includes the study of single and two-phase natural circulation loops through a bibliographical study and the simulations of the PERSEO and HERO-2 experimental facilities. After a synthetic presentation of the project and its objectives, this article provides the reader with findings related to the physical analysis of the test results obtained on the PKL and PASI installations as well an overall evaluation of the capability of the different numerical tools to simulate passive systems.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.78-88
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• 2024

Ship-radiated noise received by passive sonar that can measure underwater noise can be identified and classified ship using Detection of Envelope Modulation on Noise (DEMON) analysis. However, in a low Signal-to-Noise Ratio (SNR) environment, it is difficult to analyze and identify the target frequency line containing ship information in the DEMONgram. In this paper, we conducted a study to extract target frequency lines using semantic segmentation among deep learning techniques for more accurate target identification in a low SNR environment. The semantic segmentation models U-Net, UNet++, and DeepLabv3+ were trained and evaluated using simulated DEMONgram data generated by changing SNR and fundamental frequency, and the DEMONgram prediction performance of DeepShip, a dataset of ship-radiated noise recordings on the strait of Georgia in Canada, was compared using the trained models. As a result of evaluating the trained model with the simulated DEMONgram, it was confirmed that U-Net had the highest performance and that it was possible to extract the target frequency line of the DEMONgram made by DeepShip to some extent.