• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.227-235
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• 2022

The purpose of this study was to analyze the risk and vulnerability of marine accidents based on statistical data on marine accidents at Ulsan Port, which has the largest amount of liquid cargo in Korea. It was found to be quite vulnerable to the risk of marine accidents, environmental damage, and vulnerability to environmental pollution accidents. Based on analysis results, marine accident scenarios and accident response strategies were prepared. Additionally, as a response strategy to prepare for large-scale marine pollution accidents at Ulsan Port, it is necessary to establish control equipment and infrastructure, as well as establish a control center to integrate marine accident safety functions. In particular, in the case of liquid cargo specialized ports such as Ulsan Port, considering the size of the cargo volume and the frequency of marine pollution accidents, it is urgent to build professional safety management institutions, which should make the port safer.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.596-605
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• 2022

This study aimed to introduce research on coerced debt victimization and interventions in the context of domestic violence. To achieve the aim, this study reviewed existing studies on coerced debt conducted in the US. This study discussed the followings: First, coerced debt was theorized by coerced control theory of domestic violence and control mechanisms of economic abuse and conceptualized as fraud and force. Second, the effects of coerced debt included credit damage, economic dependence, and barriers to housing, employment, and safety. Third, to intervene the victimization, service providers should endure uncertainty and its time consuming process of recovering, provide an intense and personalized advocacy, and overcome the problems of absence of policies to support the victims. Finally, service providers should have educations and training programs on the assessment and intervention skills of coerced debt acknowledging empowerment and safety of the victims as the most important.

• Journal of Trauma and Injury
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• v.35 no.3
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• pp.215-218
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• 2022

The rectum is the least frequently injured organ in trauma, with an incidence of about 1% to 3% in trauma cases involving civilians. Most rectal injuries are caused by gunshot wounds, blunt force trauma, and stab wounds. A 46-year-old male patient was crushed between two vehicles while he was working. He was hemodynamically unstable, and the Focused Assessment with Sonography for Trauma showed hemoperitoneum and hemoretroperitoneum; therefore, damage control surgery with pelvic packing was performed. A subsequent whole-body computed tomography scan showed a displaced pelvic bone and sacrum fracture. There was evidence of an anorectal full-thickness laceration and urethral laceration. In second-look surgery performed 48 hours later, the pelvis was stabilized with external fixators, and it was decided to proceed with loop sigmoid colostomy. A tractioned rectal probe with an internal balloon was positioned in order to approach the flaps of the rectal wall laceration. On postoperative day 13, a radiological examination with endoluminal contrast injected from the stoma after removal of the balloon was performed and showed no evidence of extraluminal leak. Rectosigmoidoscopy, rectal manometry, anal sphincter electromyography, and trans-stomic transit examinations showed normal findings, indicating that it was appropriate to proceed with the closure of the colostomy. The postoperative course was uneventful. The optimal management for extraperitoneal penetrating rectal injuries continues to evolve. Primary repair with fecal diversion is the mainstay of treatment, and a conservative approach to rectal lacerations with an internal balloon in a rectal probe could provide a possibility for healing with a lower risk of complications.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3745-3765
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• 2022

The concrete structures related to nuclear safety are threatened by accidental impact loadings, mainly including the low-velocity drop-weight impact (e.g., spent fuel cask and assembly, etc. with the velocity less than 20 m/s) and high-speed projectile impact (e.g., steel pipe, valve, turbine bucket, etc. with the velocity higher than 20 m/s), while the existing studies are still limited in the impact resistant design of nuclear power plant (NPP), especially the primary RC slab. This paper aims to propose the numerical simulation and theoretical approaches to assist the impact-resistant design of RC slab in NPP. Firstly, the continuous surface cap (CSC) model parameters for concrete with the compressive strength of 20-70 MPa are fully calibrated and verified, and the refined numerical simulation approach is proposed. Secondly, the two-degree freedom (TDOF) model with considering the mutual effect of flexural and shear resistance of RC slab are developed. Furthermore, based on the low-velocity drop hammer tests and high-speed soft/hard projectile impact tests on RC slabs, the adopted numerical simulation and TDOF model approaches are fully validated by the flexural and punching shear damage, deflection, and impact force time-histories of RC slabs. Finally, as for the two low-velocity impact scenarios, the design procedure of RC slab based on TDOF model is validated and recommended. Meanwhile, as for the four actual high-speed impact scenarios, the impact-resistant design specification in Chinese code NB/T 20012-2019 is evaluated, the over conservation of which is found, and the proposed numerical approach is recommended. The present work could beneficially guide the impact-resistant design and safety assessment of NPPs against the accidental impact loadings.

• Physical Therapy Rehabilitation Science
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• v.11 no.3
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• pp.356-362
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• 2022

Objective: Extracorporeal shock wave therapy (ESWT) is a nonsurgical treatment alternative to surgery for various musculoskeletal diseases that have traditionally been difficult to treat conservatively, including calcific tendinitis, tennis elbow, and plantar fasciitis. This study evaluated the effect of focused and radial shock wave therapy for calcific tendinitis of the shoulder. Design: Randomized controlled study Methods: Forty participants with calcific tendinitis were randomized into focused shock wave therapy (FSWT, n=20) and radial shock wave therapy (RSWT, n=20) groups. Patients were examined before and one week after treatment. Pain intensity was subjectively assessed using the visual analogue scale and function was assessed using the Constant-Murley score (CMS) and range of motion (ROM). Results: The results showed a significant decrease in pain and significant increase in shoulder mobility and function in both groups. However, FSWT was significantly more effective than RSWT, based on CMS and ROM assessment. Conclusions: Although it is possible to raise the energy intensity of RSWT to increase the depth at which the energy becomes dispersed, higher energy intensity is associated with a greater risk of severe neurovascular damage, and that high-intensity stimulation can cause adverse effects such as pain and petechiae. Therefore, FSWT is considered to be a safe and effective method for treating tendinous lesions while minimizing adverse effects. In conclusion, both FSWT and RSWT can reduce pain and increase mobility and function. FSWT can be considered as an alternative for calcific tendinitis of the shoulder.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Smart Structures and Systems
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• v.29 no.1
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• Earthquakes and Structures
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• v.21 no.5
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• pp.515-530
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• 2021

In a tall reinforced concrete (RC) core wall system subjected to strong ground motions, inelastic behavior near the base as well as mid-height of the wall is possible. Generally, the formation of plastic hinge in a core wall system may lead to extensive damage and significant repairing cost. A new configuration of core structures consisting of buckling restrained braced frames (BRBFs) and RC walls is an interesting idea in tall building seismic design. This concept can be used in the plan configuration of tall core wall systems. In this study, tall buildings with different configurations of combined core systems were designed and analyzed. Nonlinear time history analysis at severe earthquake level was performed and the results were compared for different configurations. The results demonstrate that using enough BRBFs can reduce the large curvature ductility demand at the base and mid-height of RC core wall systems and also can reduce the maximum inter-story drift ratio. For a better investigation of the structural behavior, the probabilistic approach can lead to in-depth insight. Therefore, incremental dynamic analysis (IDA) curves were calculated to assess the performance. Fragility curves at different limit states were then extracted and compared. Mean IDA curves demonstrate better behavior for a combined system, compared with conventional RC core wall systems. Collapse margin ratio for a RC core wall only system and RC core with enough BRBFs were almost 1.05 and 1.92 respectively. Therefore, it appears that using one RC core wall combined with enough BRBF core is an effective idea to achieve more confidence against tall building collapse and the results demonstrated the potential of the proposed system.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.73-84
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• 2022

Background : Lymphedema is a progressive disorder characterized by the impairment of lymph flow from tissues to the blood circulation system. This occurs as a result of damage to the lymphatic system. Complex decongestive therapy (CDT) is a multimodal, conservative therapeutic approach that is used for the management of lymphedema. CDT consists of a combination of compression therapy, manual lymphatic drainage, exercise, and skin care. Purpose : This study aimed to provide a review of available physical therapy interventions as well as general care guidelines for patients with lymphedema. Methods : The recommendations and guidelines for physical therapy management, medical management, and general information were reviewed from the following sources: 1) The American Physical Therapy Association, 2) The Norton School of Lymphatic Therapy, and 3) The International Society of Lymphology. This review contains general information, including the medical management and the importance of physical therapy in lymphedema. Physical therapy management should be based on an assessment of the patients' presenting impairments, including based on inclusion or exclusion of physical therapy interventions. This review also outlines a step-by-step approach that starts with disease diagnosis and progression all the way through to rehabilitation as an outpatient. Conclusion : Depending on the patients' journey to recovery and the requirement for rehabilitation, physical therapy interventions should focus on the patients' needs including pain, appearance, physical function and general rehabilitation. We hope that this review will provide information on evidence-based physical therapy and general care to patients with lymphedema.