• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.765-778
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• 2008

Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

• Animal Bioscience
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• v.35 no.10
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• pp.1545-1555
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• 2022

Objective: Our study aimed to investigate the effects of a 2% increase in dietary total digestible nutrients (TDN) value during the growing (7 to 12 mo of age) and fattening (13 to 30 mo of age) period of Hanwoo steers. Methods: Two hundred and twenty Hanwoo steers were assigned to one of two treatments: i) a control group (basal TDN, BTDN, n = 111 steers, growing = 70.5%, early fattening = 71.0%, late fattening = 74.0%) or high TDN (HTDN, n = 109 steers, growing = 72.6%, early = 73.1%, late = 76.2%). Growth performance, carcass traits, blood parameters, and gene expression of longissimus dorsi (LD) (7, 18, and 30 mo) were quantified. Results: Steers on the BTDN diets had increased (p≤0.02) DMI throughout the feeding trial compared to HTDN, but gain did not differ appreciably. A greater proportion of cattle in HTDN received Korean quality grade 1 (82%) or greater compared to BTDN (77%), while HTDN had a greater yield grade (29%) than BTDN (20%). Redness (a^*) of LD muscle was improved (p = 0.021) in steers fed HTDN. Feeding the HTDN diet did not alter blood parameters. Steers fed HTDN diet increased (p = 0.015) the proportion of stearic acid and tended to alter linoleic acid. Overall, saturated, unsaturated, monounsaturated, and polyunsaturated fatty acids of LD muscle were not impacted by the HTDN treatment. A treatment by age interaction was noted for mRNA expression of myosin heavy chain (MHC) IIA, IIX, and stearoyl CoA desaturase (SCD) (p≤0.026). No treatment effect was detected on gene expression from LD muscle biopsies at 7, 18, and 30 mo of age; however, an age effect was detected for all variables measured (p≤0.001). Conclusion: Our results indicated that feeding HTDN diet could improve overall quality grade while minimum effects were noted in gene expression, blood parameters, and growing performance. Cattle performance prediction in the feedlot is a critical decision-making tool for optimal planning of cattle fattening and these data provide both benchmark physiological parameters and growth performance measures for Hanwoo cattle feeding enterprises.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.459-471
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• 2023

This study identified the characteristics of changes in forest areas of North Korea's major regions (Gaesong, Goseong, Pyongyang, and Hyesan·Samsu) using data on degraded lands collected via monitoring by the National Institute of Forest Science. The data, spanning 1999 to 2018, were cross-analyzed to determine trends in land cover change, and hotspot analysis was conducted to confirm evident changes in the forest areas. The results showed that the areas of interest substantially transitioned to other land use types from 1999 to 2008. Contrastingly, the range of changes decreased from 2008 to 2018, with some areas regenerating into forests. Nevertheless, the hotspot analysis indicated that hotspots occurred more intensively in the outskirts of cities and forest edges from 2008 to 2018 than from 1999 to 2008. The analysis also showed that the aforementioned changes were caused by various aspects, depending on regional characteristics and social factors. This study can be used as a basic reference for decision-making on the selection of basic forest restoration targets and restoration methods in inter-Korean forest cooperation initiatives.

• Journal of Korean Neurosurgical Society
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• v.67 no.1
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

• 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.

• Journal of Chest Surgery
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• v.57 no.1
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• pp.62-69
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• 2024

Background: Cervical esophageal cancer is a rare malignancy that requires specialized care. While definitive chemoradiation is the standard treatment approach, surgery remains a valuable option for certain patients. This study examined the surgical outcomes of patients with cervical esophageal cancer. Methods: The study involved a retrospective review and analysis of 24 patients with cervical esophageal cancer. These patients underwent surgical resection between September 1994 and December 2018. Results: The mean age of the patients was 61.0±10.2 years, and 22 (91.7%) of them were male. Furthermore, 21 patients (87.5%) had T3 or T4 tumors, and 11 (45.8%) exhibited lymph node metastasis. Gastric pull-up with esophagectomy was performed for 19 patients (79.2%), while 5 (20.8%) underwent free jejunal graft with cervical esophagectomy. The 30-day operative mortality rate was 8.3%. During the follow-up period, complications included leakage at the anastomotic site in 9 cases (37.5%) and graft necrosis of the gastric conduit in 1 case. Progression to oral feeding was achieved in 20 patients (83.3%). Fifteen patients (62.5%) displayed tumor recurrence. The median time from surgery to recurrence was 10.5 months, and the 1-year recurrence rate was 73.3%. The 1-year and 3-year survival rates were 75% and 33.3%, respectively, with a median survival period of 17 months. Conclusion: Patients with cervical esophageal cancer who underwent surgical resection faced unfavorable outcomes and relatively poor survival. The selection of cases and decision to proceed with surgery should be made cautiously, considering the risk of severe complications.

• Journal of Chest Surgery
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• v.57 no.2
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• pp.160-168
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• 2024

Background: Data on perioperative outcomes of emergent versus elective resection in esophageal cancer patients requiring esophagectomy are lacking. We investigated whether emergent resection was associated with increased risks of morbidity and mortality. Methods: Data on patients with esophageal malignancy who underwent esophagectomy from 2005 to 2020 were retrospectively analyzed from the American College of Surgeons National Surgical Quality Improvement Program database. Thirty-day complication and mortality rates were compared between emergent esophagectomy (EE) and non-emergent esophagectomy. Logistic regression assessed factors associated with complications and mortality. Results: Of 10,067 patients with malignancy who underwent esophagectomy, 181 (1.8%) had EE, 64% had preoperative systemic inflammatory response syndrome, sepsis, or septic shock, and 44% had bleeding requiring transfusion. The EE group had higher American Society of Anesthesiologists (ASA) class and functional dependency. More transhiatal esophagectomies and diversions were performed in the EE group. After EE, the rates of 30-day mortality (6.1% vs. 2.8%), overall complications (65.2% vs. 44.2%), bleeding, pneumonia, prolonged intubation, and positive margin (17.7% vs. 7.4%) were higher, while that of anastomotic leak was similar. On adjusted logistic regression, older age, lower albumin, higher ASA class, and fragility were associated with increased complications and mortality. McKeown esophagectomy and esophageal diversion were associated with a higher risk of postoperative complications. EE was associated with 30-day postoperative complications (odds ratio, 2.39; 95% confidence interval, 1.66-3.43; p<0.0001). Conclusion: EE was associated with a more than 2-fold increase in complications compared to elective procedures, but no independent increase in short-term mortality. These findings may help guide data-driven critical decision-making for surgery in select cases of complicated esophageal malignancy.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.

• Information Systems Review
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• v.23 no.1
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• pp.45-68
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• 2021

As the influence of online reviews on consumer decision-making increases, concerns about review manipulation are also increasing. Fake reviews or review manipulations are emerging as an important problem by posting untrue reviews in order to increase sales volume, causing the consumer's reverse choice, and acting at a high cost to the society as a whole. Most of the related prior studies have focused on predicting review manipulation through data mining methods, and research from a consumer perspective is insufficient. However, since the possibility of manipulation of reviews perceived by consumers can affect the usefulness of reviews, it can provide important implications for online word-of-mouth management regardless of whether it is false or not. Therefore, in this study, we analyzed whether there is a difference between the review evaluated by the consumer as being manipulated and the general review, and verified whether the manipulated review negatively affects the review usefulness. For empirical analysis, 34,711 online book reviews on the LibraryThing website were analyzed using multilevel logistic regression analysis and Poisson regression analysis. As a result of the analysis, it was found that there were differences in product level, reviewer level, and review level factors between reviews that consumers perceived as being manipulated and reviews that were not. In addition, manipulated reviews have been shown to negatively affect review usefulness.