• The Journal of Korean Medicine
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• v.43 no.2
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• pp.75-91
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• 2022

Objectives: The purpose of this overview was to summarize the evidence regarding the effectiveness of Cognitive Behavioral Therapy (CBT) for sleep disorders through systematic reviews (SRs) and meta-analyses (MAs). Methods: An overview of systematic review was conducted according to the study protocol (reviewregistry1320). A comprehensive literature search was performed using three databases (Pubmed, Cochrane Central Register of Controlled Trials, and Web of Science) and three Korean databases (KoreaMed, KMbase, and ScienceON). Final studies were selected by three authors according to inclusion and exclusion criteria, and data needed for analysis were extracted by a pre-planned extraction framework. Methodological quality of systematic review was assessed using the 'Assessment of multiple systematic reviews 2 (AMSTAR2)'. Results: Fourteen SRs and MAs were included, of which eleven SRs were performed MAs. Twelve studies studied insomnia among sleep disorders, and the rest are nightmares and sleep disturbances with PTSD. Ten studies reported the effect of CBT on sleep disorders measured by insomnia severity index (ISI) and sleep onset latency (SOL), and all reported a significant improvement effect. Eight studies reported the effect of CBT on sleep disorders measured by wake time after sleep onset (WASO), and seven studies reported a significant improvement effect. The methodological quality of the studies evaluated with AMSTAR 2 was mainly low or very low because of omission of protocol registration and excluded study list. Conclusions: Practical guidelines and studies show that CBT is effective for sleep disorders, but access to CBT needs to be improved.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.401-407
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• 2022

Electronic media are an integral part of modern civilization; educational practices are no exception, which should change the content orientations, structures and methodological approaches in accordance with the requirements of the educational market. This makes it relevant to find effective and successful configurations in the process of implementing modern educational practices. The purpose of the research lies in determining the basic principles of electronic media and their place in modern education, identifying the effectiveness of teaching disciplines with application of electronic media, as well as establishing the level of assessment by students of the need to involve different types of electronic media in the educational process and professional practice. The research methodology is complex; the descriptive method and methods of observation, analysis and synthesis have been used in the academic paper. The method of pedagogical experiment has become the principal one; the method of questionnaires and statistical methods have been also used. The hypothesis of the academic paper lies in the fact that the involvement of electronic media in the educational process makes it more effective and requires conceptual changes in educational practices. The result of the research manifests in the identification of new opportunities for the use of electronic media, leading to conceptual shifts in the framework of modern educational policies. In the future, it will be appropriate to consider the theoretical aspects of changing worldview models in education and the use of new media in the educational process, their effectiveness and relevance.

• 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.

• The korean journal of orthodontics
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• v.52 no.5
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• pp.313-323
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• 2022

Objective: This study aimed to estimate the clinical effects of different types of bone-anchored maxillary protraction devices by using a network meta-analysis. Methods: We searched seven databases for randomized and controlled clinical trials that compared bone-anchored maxillary protraction with tooth-anchored maxillary protraction interventions or untreated groups up to May 2021. After literature selection, data extraction, and quality assessment, we calculated the mean differences, 95% confidence intervals, and surface under the cumulative ranking scores of eleven indicators. Statistical analysis was performed using R statistical software with the GeMTC package based on the Bayesian framework. Results: Six interventions and 667 patients were involved in 18 studies. In comparison with the tooth-anchored groups, the bone-anchored groups showed significantly more increases in Sella-Nasion-Subspinale (°), Subspinale-Nasion-Supramentale(°) and significantly fewer increases in mandibular plane angle and the labial proclination angle of upper incisors. In comparison with the control group, Sella-Nasion-Supramentale(°) decreased without any statistical significance in all treated groups. IMPA (angle of lower incisors and mandibular plane) decreased in groups with facemasks and increased in other groups. Conclusions: Bone-anchored maxillary protraction can promote greater maxillary forward movement and correct the Class III intermaxillary relationship better, in addition to showing less clockwise rotation of mandible and labial proclination of upper incisors. However, strengthening anchorage could not inhibit mandibular growth better and the lingual inclination of lower incisors caused by the treatment is related to the use of a facemask.

• Journal of Korean Society on Water Environment
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• v.38 no.4
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• pp.177-189
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• 2022

Nature-based Solutions (NbS) are defined as practical and technical approaches to restoring functioning ecosystems and biodiversity as a means to address socio-environmental challenges and provide human-nature co-benefits. This study reviews NbS-related literature to identify its key characteristics, techniques, and challenges for its application in climate-adaptive water management. The review finds that NbS has been commonly used as an umbrella term incorporating a wide range of existing ecosystem-based approaches such as low-impact development (LID), best management practices (BMP), forest landscape restoration (FLR), and blue-green infrastructure (BGI), rather than being a uniquely-situated practice. Its technical form and operation can vary significantly depending on the spatial scale (small versus large), objective (mitigation, adaptation, naturalization), and problem (water supply, quality, flooding). Commonly cited techniques include green spaces, permeable surfaces, wetlands, infiltration ponds, and riparian buffers in urban sites, while afforestation, floodplain restoration, and reed beds appear common in non- and less-urban settings. There is a greater lack of operational clarity for large-scale NbS than for small-scale NbS in urban areas. NbS can be a powerful tool that enables an integrated and coordinated action embracing not only water management, but also microclimate moderation, ecosystem conservation, and emissions reduction. This study points out the importance of developing decision-making guidelines that can inform practitioners of the selection, operation, and evaluation of NbS for specific sites. The absence of this framework is one of the obstacles to mainstreaming NbS for water management. More case studies are needed for empirical assessment of NbS.

• PNF and Movement
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• v.20 no.3
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• pp.359-370
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• 2022

Purpose: Physical therapists are required to properly choose the most appropriate treatment for each patient within the framework of the International Classification of Functioning, Disability, and Health (ICF model). The aims of this study were to determine whether neurological physical therapists in clinical settings in South Korea know about the ICF model and to investigate the current trends of outcome measures (OMs) used by them. Methods: Two hundred and one physical therapists who worked with patients with neurological disorders participated in this study. The survey was conducted via e-mail and asked about commonly used OMs and the considerations for selecting OMs. Results: All physical therapists involved in this study responded completely, and 45.8% of participants learned about the ICF model, while 37.3% understood the detailed information related to the ICF model. The rest of the participants did not know or just heard about the ICF model. The most frequently used tools at the body function/structure level were the Range of Motion (98%), Manual Muscle Test (97%), Berg Balance Scale (83.1%), and Modified Ashworth Scale (70.6%) when allowing repetition. At the activity level, the 10-meter walk test (71.1%), 6-minute walk test (54.2%), and Functional Ambulatory Category (43.3%) were used, while the Activity-Specific Balance Confidence Scale (23.9%) was used at the participation level. There was a positive relationship between the number of tools used and years of work, as well as the level of understanding of the ICF model. Conclusion: The results of this study suggest that it is necessary to learn the ICF model in a clinical setting. In addition, the medical system needs to be modified to encourage physical therapists in South Korea to use proper OMs within the ICF model.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.4
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• pp.423-435
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• 2021

Purpose: The purpose of this study is to identify the educational needs of a severe trauma treatment simulation program based on mixed reality which combines element of both virtual reality and augmented reality. Methods: Focus group interviews were conducted with ten military hospital nurses on February 4 and 5, 2021. The collected data were analyzed using a qualitative content analysis. As a framework for data analysis, the educational needs were clustered into the following four categories: teaching contents, teaching methods, teaching evaluation, and teaching environment. Results: The educational needs for each category that emerged were as follows: three subcategories including "realistic education reflecting actual clinical practice" and "motivating education" for teaching contents; five subcategories including "team-based education," "repeated education that acts as embodied learning," and "stepwise education" for teaching methods; six subcategories including "debriefing through video conferences," "team evaluation and evaluator in charge of the team," "combination of knowledge and practice evaluation" for teaching evaluation; six subcategories including "securing safety," "similar settings to real clinical environments," "securing of convenience and accessibility for learners," and "operating as continuing education" for teaching environment. Conclusion: The findings of this study can provide a guide for the development and operation of a severe trauma treatment simulation program based on mixed reality. Moreover, it suggests that research to identify the educational needs of various learners should be conducted.

• Women's Health Nursing
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• v.28 no.2
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• pp.87-99
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• 2022

Purpose: The purpose of this systematic review was to examine aromatherapy interventions for prenatal and postnatal women, and to determine the effectiveness of these interventions on fatigue. Methods: Six national and international databases were reviewed to retrieve and collect studies published up to September 7, 2021, describing randomized controlled trials and controlled clinical trials of aromatherapy interventions for prenatal and postnatal women's fatigue. Of the 323 articles initially identified, 64 duplicates were excluded and 259 were screened. After further excluding 216 articles not related to PICO framework, 10 were selected for review. Two reviewers independently selected studies and conducted data extraction and quality appraisal using Cochran's Risk of Bias and Risk of Bias Assessment Tool for Non-randomized Studies. Results: The quality of the 10 selected studies was overall satisfactory. A meta-analysis of three studies showed that aromatherapy with lavender oil produced a 0.75-point reduction in postnatal mothers' fatigue when compared to control groups. Sleep quality was also analyzed as a secondary outcome of fatigue. A meta-analysis of four studies using lavender and/or orange peel oil found that aromatherapy produced a 0.98-point improvement in postnatal mothers' quality of sleep. Although a meta-analysis could not be conducted to synthesize the findings for fatigue in pregnant women, inhalation and massage therapy using lavender oil showed positive effects on prenatal fatigue and sleep quality. Conclusion: Aromatherapy using lavender oil and orange peel oil is effective in improving prenatal and postnatal fatigue and sleep quality.

• Smart Structures and Systems
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• v.31 no.4
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• pp.365-381
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• 2023

The existing vision-based techniques for inspection and condition assessment of civil infrastructure are mostly manual and consequently time-consuming, expensive, subjective, and risky. As a viable alternative, researchers in the past resorted to deep learning-based autonomous damage detection algorithms for expedited post-disaster reconnaissance of structures. Although a number of automatic damage detection algorithms have been proposed, the scarcity of labeled training data remains a major concern. To address this issue, this study proposed a semi-supervised learning (SSL) framework based on consistency regularization and cross-supervision. Image data from post-earthquake reconnaissance, that contains cracks, spalling, and exposed rebars are used to evaluate the proposed solution. Experiments are carried out under different data partition protocols, and it is shown that the proposed SSL method can make use of unlabeled images to enhance the segmentation performance when limited amount of ground truth labels are provided. This study also proposes DeepLab-AASPP and modified versions of U-Net++ based on channel-wise attention mechanism to better segment the components and damage areas from images of reinforced concrete buildings. The channel-wise attention mechanism can effectively improve the performance of the network by dynamically scaling the feature maps so that the networks can focus on more informative feature maps in the concatenation layer. The proposed DeepLab-AASPP achieves the best performance on component segmentation and damage state segmentation tasks with mIoU scores of 0.9850 and 0.7032, respectively. For crack, spalling, and rebar segmentation tasks, modified U-Net++ obtains the best performance with Igou scores (excluding the background pixels) of 0.5449, 0.9375, and 0.5018, respectively. The proposed architectures win the second place in IC-SHM2021 competition in all five tasks of Project 2.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.162-162
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• 2023

Climate change is a complex phenomenon having its impact on diverse sectors. Temperature and precipitation are two of the most fundamental variables used to characterize climate, and changes in these variables can have significant impacts on ecosystems, agriculture, and human societies. This study evaluated the historical (1981-2010) and future (2011-2100) climatic trends in the Seti-Gandaki basin of Nepal based on 5 km resolution Multi Model Ensemble (MME) of 18 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for SSP1-2.6, SSP2-4.5 and SSP5-85 scenarios. For this study, ERA5 reanalysis dataset is used for historical reference dataset instead of observation dataset due to a lack of good observation data in the study area. Results show that the basin has experienced continuous warming and an increased precipitation pattern in the historical period, and this rising trend is projected to be more prominent in the future. The Seti basin hosts 13 operational hydropower projects of different sizes, with 10 more planned by the government. Consequently, the findings of this study could be leveraged to design adaptation measures for existing hydropower schemes and provide a framework for policymakers to formulate climate change policies in the region. Furthermore, the methodology employed in this research could be replicated in other parts of the country to generate precise climate projections and offer guidance to policymakers in devising sustainable development plans for sectors like irrigation and hydropower.