• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.99-107
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• 2020

Fibromyalgia is a disorder characterized by the core symptom of chronic widespread pain, along with fatigue, sleep disturbances, mood changes, and cognitive difficulties. The etiology of fibromyalgia involves a combination of biological factors, such as genetic vulnerability, alterations in pain processing and stress response system ; psychological factors, such as anxiety, depression, anger, and perceived stress ; environmental factors, such as infections, febrile diseases, and trauma. Central sensitization, which is amplified in the process of sensory stimulation, has been emphasized as a key etiological factor, as supported by enhanced wind-up, delayed aftersensation, decreased nociceptive flexion reflex threshold and functional imaging studies. Several guidelines recommend that a multimodal approach be used to treat fibromyalgia, including both pharmacological and non-pharmacological treatments, tailored to each individual, and that clinicians should provide an intellectual framework through sufficient education and emphasis on the importance of self-management. The prevalence of mood disorders, anxiety disorders, and other psychiatric problems is 7-9 times higher in patients with fibromyalgia than in the general population ; moreover, the association between fibromyalgia and certain psychopathologies or sleep problems has also been suggested. Since psychiatric problems, with shared vulnerabilities and risk factors, interact with fibromyalgia bidirectionally and also affect the disease course, an integrated management approach is needed to determine the risk of comorbidities.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.309-316
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• 2022

In order to minimize the human and time consumption required for rock classification, research on rock classification using artificial intelligence (AI) has recently developed. In this study, basic volcanic rocks were subdivided by using polarizing microscope thin section images. A convolutional neural network (CNN) model based on Tensorflow and Keras libraries was self-producted for rock classification. A total of 720 images of olivine basalt, basaltic andesite, olivine tholeiite, trachytic olivine basalt reference specimens were mounted with open nicol, cross nicol, and adding gypsum plates, and trained at the training : test = 7 : 3 ratio. As a result of machine learning, the classification accuracy was over 80-90%. When we confirmed the classification accuracy of each AI model, it is expected that the rock classification method of this model will not be much different from the rock classification process of a geologist. Furthermore, if not only this model but also models that subdivide more diverse rock types are produced and integrated, the AI model that satisfies both the speed of data classification and the accessibility of non-experts can be developed, thereby providing a new framework for basic petrology research.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.4
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• pp.1-18
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• 2021

Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.3
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• pp.13-27
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• 2022

Objectives This study investigated the trends in domestic and international clinical research in craniosacral therapy, classified as a type of Chuna manual therapy, and suggested further directions in Korean medicine. Methods This scoping review was performed using the Arksey and O'Malley methodological framework and preferred reporting items as per the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews checklist. Eight electronic databases (PubMed, EMBASE, Cochrane Library, Koreanstudies Information Service System [KISS], KMBASE, Oriental Medicine Advanced Searching Integrated System [OASIS], Research Information Sharing Service [RISS], ScienceON) were searched to identify articles with the search terms "craniosacral therapy" and "cranial osteopathy" until December 2021. Results Forty-five studies were eligible as per our inclusion criteria. Most research studies (n=44) were conducted in the field of medicine and pharmacy, especially in rehabilitation medicine (n=16). As a result of the study design, randomized controlled trials (n=20) were the most common, and chronic pain (n=9) was the most frequently targeted disease, followed by headache (n=7). Thirty-two studies suggested interventions and 20 studies used Upledger's 10-step protocol. The average duration of craniosacral therapy was 41 min per session, administered 1.4 times per week. Outcome measurements were analyzed and categorized with the examination procedure for the patient. Conclusions This is the first scoping review of craniosacral therapy in Korea, and we believe that our findings could support its utility as Chuna. In the future, more studies should be conducted to establish the evidence of clinical efficacy of craniosacral therapy and develop standard techniques in Korean medicine.

• Iberoamérica
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• v.22 no.1
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• pp.31-72
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• 2020

This study examines the concepts and policy factors regarding gender-mainstreaming strategies and urban areas that have been discussed in the fields of international norms and development cooperation from the perspective of the Mexican government. It analyzes how gender-mainstreaming strategy is integrated and realized through Mexican law and key programs carried out by Mexico City. Through a literature review, this study builds upon previous research and theoretical discussions. In fact, Mexican federal government is considered to have successfully achieved "gender institutionalization." Within the framework of the law and institutions, the programs promoted by Mexico City aim to realize women's rights and meet their needs in the metropolis, while emphasizing a wider participation by citizens to realize these urban rights. In particular, the government of Mexico City is expanding on policies and programs that focus on strengthening the financial autonomy of women by understanding women's vulnerabilities as inequalities arising in the areas of the economy, space, and time.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.1
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• pp.107-124
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• 2022

Objectives This study aimed to identify optimal combinations of acupoints used to treat chemotherapy-induced peripheral neuropathy (CIPN). Methods We searched four international databases (MEDLINE, EMBASE, the Allied and Complementary Medicine Databases [AMED], and China National Knowledge Infrastructure [CNKI]) and five Korean databases (DBpia, Research Information Sharing Service [RISS], Korean Studies Information Service System [KISS], Oriental Medicine Advanced Searching Integrated System [OASIS], and KoreaMed) to identify randomized controlled trials (RCTs) that used acupuncture to treat CIPN. Network analysis was performed on the acupoints used in more than three included articles. We constructed a network by calculating the Jaccard similarity coefficient between acupoints and applied minimum spanning tree. Then, modularity analysis, degree centrality (Cd), and betweenness centrality (Cb) were used to analyze properties of the acupoints. Results A total of 25 articles were included. 24 acupoints were extracted from 25 articles. The combinations of acupoints having the highest Jaccard similarity coefficient were {EX-UE9, EX-LE10} and {ST36, SP6}. In the modularity analysis, acupoints were classified to six modules. ST40, EX-UE11, and KI6 had the highest Cd value while ST40, GB34 had the highest Cb value. Conclusions This study found the systematic framework of acupoint combinations used in CIPN studies. This study is expected to provide new perspectives of CIPN treatment to therapists. A RCT is in progress of using the network of this study as a guideline. If significant results are derived from the RCT, it will be possible to lay the groundwork to consider acupuncture for CIPN treatment.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.1-12
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• 2022

Since the early 20th century, along with the interest and development of alternative psychotherapy, the field of art therapy has also been developed and expanded. In particular, the recent development of technology and the untact era brought about by the COVID-19 Pandemic is accelerating the development of new digital art therapy contents. Among them, the hot interest in virtual reality is raising expectations and questions about the effectiveness of psychotherapy given by new media beyond traditional art therapy. In this study, the characteristics of VRAT (Virtual Reality Art Therapy) content therapeutic factors were investigated through qualitative literature analysis based on the conceptual framework and therapeutic components of ETC (Expressive Therapies Continumm), an integrated art therapy theory. As a result of the study, VRAT contents showed mostly therapeutic factors in the left hemisphere that triggered the user's dynamic, perceptual, and cognitive factors, and the therapeutic factors in the right hemisphere, which focused on sensory, emotional, and symbolic factors, were relatively few. The reason seems to be due to the nature of the experimental stage, the absence of active intervention by the therapist and long-term session composition, and the fear, clumsiness, and unfamiliarity of users about VRAT in addition to the characteristics and technical limitations of the VRAT medium. The limitations of the study include the small number of documents to be analyzed and the insufficient form of current VRAT to be called art therapy. It is expected that the characteristics of the therapeutic factors of VRAT content media and environment derived as a result of this study will be usefully used for the appropriate development of VRAT content in the future.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1115-1124
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• 2022

The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.11-17
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• 2022

In this study, we address the development of a floating platform system based on a unmanned surface vessel for wide-area sensing and monitoring of hazardous and noxious substances (HNSs). For long endurance, a movable floating platform with no mooring lines was used and modified for HNS sensing and monitoring. The floating platform was equipped with various sensors such as optical and thermal imaging cameras, marine radar, and sensors for detecting HNSs in water and air. Additionally, for experiment validation in real outdoor environments, a portable gas-exposure system (PGS) was built and installed on the monitoring system. The software for carrying out the mission was integrated with the Robot Operating System (ROS) framework. The practical feasibility of the developed system was verified through experimental tests conducted in inland water and real-sea environments.