• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.551-559
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• 2019

Since 2000, many local governments have been trying to introduce trams because of the government's failure to adopt environment-friendly policies and light rail. However, there is no service evaluation system that can maintain and enhance tram users' convenience, safety, and comfort during operation. In addition, the tram characteristics are not reflected in the application of the evaluation system of "management and service evaluation for public transportation operators" which is being implemented to railway operators or bus transportation operators. The purpose of this study is to develop the evaluation criteria of operating service according to tram operation model. First, we reviewed cases related to the evaluation of operating services in roads, buses, railways, and airways. And the evaluation criteria and the evaluation items are presented. This study is expected to help to secure and improve operational service in the operation phase of the tram that will be introduced in the future.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.19-30
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• 2021

This study evaluated the injection rate and the injection efficiency of the artificial recharge in the upper drought-prone watershed region, where the remaining water was used for injection, by using a numerical model to secure water during a drought. As a result of a numerical model under the condition of diverse injection rates per a well and hydraulic characteristics of the aquifer, the optimal injection rate per a well was estimated as 50.0 ㎥/day, and the injection efficiency was simulated as 33.2% to 81.2% of the total injection volume. As the injection time was shorter, the injection efficiency tented to increase non-linearly. As the injection rate increased, the residual storage in aquifer increased and available groundwater amount also increased, which could be advantageous for drought relief. For a more accurate assessment of injection efficiency, the model will be validated using the field injection data and optimum scenarios will enable the efficient operation of the artificial recharge system in the study area.

• Smart Structures and Systems
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• v.30 no.1
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• pp.75-88
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• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• Korean Journal of Clinical Pharmacy
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• v.32 no.1
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• pp.37-46
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• 2022

Background: Non-valvular atrial fibrillation (NVAF) is associated with ischemic stroke risk in the aging population. Observational studies have indicated beneficial effects of direct-acting oral anticoagulant (DOAC) against ischemic stroke compared to warfarin. This study aimed to investigate ischemic stroke incidence and bleeding risk in patients on DOAC therapy. Methods: Using the database of Korean Health Insurance Review and Assessment-Aged Patient Sample 2015, we conducted a retrospective cohort study. Study subjects with NVAF diagnosis and prescribed anticoagulants were enrolled. Propensity score (PS) matching by age, sex, comorbidities, and medications were used. The clinical outcomes were major adverse cerebro-cardiovascular events (MACCEs, ischemic stroke/systemic embolism, myocardial infarction, cardiac death) and bleeding events. A cox proportional hazard model analysis was performed to compare the outcomes with hazard ratio (HR) and 95% confidence interval (CI). Results: Total 4,773 elderly patients with NVAF were initially included. Four PS-matched groups including rivaroxaban vs. warfarin-only (n=1,079), dabigatran vs. warfarin-only (n=721), rivaroxaban vs. dabigatran (n=721), and switchers of warfarin to rivaroxaban vs. warfarin-only (n=287) were analyzed. Every group showed statistically similar results of MACCEs and bleeding events, except for the group of rivaroxaban vs. dabigatran. Rivaroxaban users showed higher risks of bleeding events than dabigatran users (HR 2.25, 95% CI 1.01-4.99). Conclusion: In the elderly patients with NVAF, efficacy and safety outcomes among oral anticoagulants including DOACs and warfarin were similar, while rivaroxaban are more likely to have higher bleeding risks than dabigatran. Further research using large size sample is needed.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.47-55
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• 2023

This paper presents a method for predicting the threat index of combat systems using Gradient Boosting Regressors and Support Vector Regressors among machine learning models. Currently, combat systems are software that emphasizes safety and reliability, so the application of AI technology that is not guaranteed to be reliable is restricted by policy, and as a result, the electrified domestic combat systems are not equipped with AI technology. However, in order to respond to the policy direction of the Ministry of National Defense, which aims to electrify AI, we conducted a study to secure the basic technology required for the application of machine learning in combat systems. After collecting the data required for threat index evaluation, the study determined the prediction accuracy of the trained model by processing and refining the data, selecting the machine learning model, and selecting the optimal hyper-parameters. As a result, the model score for the test data was over 99 points, confirming the applicability of machine learning models to combat systems.

• PNF and Movement
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• v.22 no.1
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• pp.43-54
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• 2024

Purpose: Falls among persons older than 65 years are a significant concern due to their frequency and severity. This study aimed to develop a vest-type embedded artificial intelligence (AI) system capable of detecting and predicting falls in various scenarios. Methods: In this study, we established and developed a vest-type embedded AI system to judge and predict falls in various directions and situations. To train the AI, we collected data using acceleration and gyroscope values from a six-axis sensor attached to the seventh cervical and the second sacral vertebrae of the user, considering accurate motion analysis of the human body. The model was constructed using a neural network-based AI prediction algorithm to anticipate the direction of falls using the collected pedestrian data. Results: We focused on developing a lightweight and efficient fall prediction model for integration into an embedded AI algorithm system, ensuring real-time network optimization. Our results showed that the accuracy of fall occurrence and direction prediction using the trained fall prediction model was 89.0% and 78.8%, respectively. Furthermore, the fall occurrence and direction prediction accuracy of the model quantized for embedded porting was 87.0 % and 75.5 %, respectively. Conclusion: The developed fall detection and prediction system, designed as a vest-type with an embedded AI algorithm, offers the potential to provide real-time feedback to pedestrians in clinical settings and proactively prepare for accidents.

• Steel and Composite Structures
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• v.51 no.4
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• pp.351-361
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• 2024

Accurate measurement of K_IC values for gas pipeline steels is important for assessing pipe safety using failure assessment diagrams. As direct measurement of K_IC was impossible for the API X70 pipeline steel, multi-specimen fracture tests were conducted to measure J_IC using three-point bend geometry. The J values were calculated from load-displacement (F-δ) plots, and the associated crack extensions were measured from the fracture surface of test specimens. Valid data points were found for the constructed J-Δa plot resulting in J_IC=356kN/m. More data points were added analytically to the J-Δa plot to increase the number of data points without performing additional experiments for different J-Δa zones where test data was unavailable. Consequently, displacement (δ) and crack-growth (Δa) from multi-specimen tests (with small displacements) were used simultaneously, resulting in the variation of Δa-δ (crack growth law) and δ-Δa obtained for this steel. For new Δa values, corresponding δ values were first calculated from δ-Δa. Then, corresponding J values for the obtained δ values were calculated from the area under the F-δ record of a full-fractured specimen (with large displacement). Given Δa and J values for new data points, the developed J-Δa plot with extra data points yielded a satisfactory estimation of J_IC=345kN/m with only a -3.1% error. This is promising and showed that the developed technique could ease the estimation of J_IC significantly and reduce the time and cost of expensive extra fracture toughness tests.

• Korean Journal of Clinical Pharmacy
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• v.25 no.2
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• pp.120-129
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• 2015

Objectives: Drug utilization review program in Korea has provided 'drug combinations to avoid (DCA)' alerts to physicians and pharmacists to prevent potential adverse drug events or inappropriate drug use. Seven hundred and six DCA pairs have been announced officially by the Ministry of Food and Drug Safety (MFDS) by March, 2015. Some DCA pairs could be grouped based on the drug interaction mechanism and its consequences. This study aimed to investigate the drug-drug interaction (DDI) pairs, which may be potential DCAs, generated by the drug class-drug class interaction method. Methods: Eleven additive/synergistic and one antagonistic drug class-drug class interaction groups were identified. By combining drugs of two interacting drug class groups, numerous DDI pairs were made. The status and severity of DDI pairs were examined using Lexicomp and Micromedex. Also, the DCA listing rate was calculated. Results: Among 258 DDI pairs generated by the drug class-drug class interaction method, only 142 pairs were identified as official DCA pairs by the MFDS. One hundred and four pairs were identified as potential DCA pairs to be listed. QT prolonging agents-QT prolonging agents, triptans-ergot alkaloids, tricyclic antidepressants-monoamine oxidase inhibitors, and dopamine agonists-dopamine antagonists were identified as drug class-drug class interaction groups which have less than 50 % DCA listing rate. Conclusion: To improve the clinicians' adaptability to DCA alerts, the list of DCA pairs needs to be continuously updated.

• Journal of the Society of Disaster Information
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• v.8 no.1
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• pp.36-46
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• 2012

After the east Japan earthquake last March 2011, social interests are intensified in the area of increasing the earthquake resistant ability and the necessity of design method that can minimize the damage from earthquake. If bridges are damaged or collapsed, the social and economic effects are so severe that the evaluation of earthquake resistant ability becomes very important. The reviewing methods for earthquake resistant ability are many, but majority of these methods are deterministic. Thus, for the safety assessment of structures for earthquake, the method for evaluating fragility according to the stage of damage is necessary. In this paper, the fragility curves for PSC Box Girder bridge using LRB and RFPB are constructed for PGA, PGV, SA, SV, SI and the two isolators are compared.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.3
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• pp.307-314
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• 2013

Objectives: The aim of this study was to determine the prevalence of symptoms relating to musculoskeletal disorders (MSDs) and investigate the risk factors among researchers at university laboratories. Methods: 209 researchers were included in this study, drawn from 27 laboratories at three universities in Korea. Checklists for MSD symptoms and risk factor assessment were utilized. Results: The symptoms checklist showed reliable results with Cohen's Kappa 0.33-0.56, percent agreement 81.0-96.8%, and correlation coefficient 0.41-0.63. The overall prevalence of MSD symptoms was 68.9%, while the prevalence in specific parts of body were as follows: shoulders (47.6%), lower back (46.9%), neck (46.9%), knees (25.4%), wrists (20.1%), elbows (13.6%). The symptom prevalence among women was higher than among men (OR 2.67, 95% CI 1.37-5.18). Daily exposure time was observed to be a significant risk factor for developing MSD symptoms (OR 2.14-6.07). Conclusions: This study suggested that repetitive pipetting and static work posture are the most significant risk factors for MSD symptoms among laboratory researchers.