• Journal of the Korean Society of Physical Medicine
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• v.17 no.1
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• pp.75-83
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• 2022

PURPOSE: This study was conducted to investigate the effect of the resistance respiratory muscle exercise with transcutaneous electrical nerve stimulation (TENS) on the respiratory muscle tone and pulmonary function of stroke patients. METHODS: Twenty stroke patients were divided into the TENS group (n = 7), placebo TENS group (n = 7), and control group (n = 6), and each intervention was performed on the three groups 5 times a week for 4 weeks. The assessment was carried out by measuring changes in the muscle tone of the latissimus dorsi and abdominal external obliques, and pulmonary function. RESULTS: In this study, the TENS group and the placebo TENS group had significant increases in the paretic side latissimus dorsi muscle tone, forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and peak expiratory flow (PEF). There was no significant difference in changes in respiratory muscle tone between the three groups. The pulmonary function was significantly different between the three groups, and it was observed from the results of the post-hoc test that FVC showed a significant increase in the TENS group and the placebo TENS group compared to the control group. CONCLUSION: Through this study, it was found that the respiratory muscle resistance exercise was more effective as a method to increase respiratory muscle tone and pulmonary function in stroke patients than combined transcutaneous electrical nerve stimulation.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.61-69
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• 2022

Posttraumatic growth literature has been rapidly expanding in multiple academic disciplines. Purpose of this study is to examine the knowledge structure of posttraumatic growth utilizing a network analysis. Papers published between 1996 and 2018 were searched on the Web of Science, focusing on terms related to posttraumatic growth. One thousand six-hundred and fifty-nine keywords were published 6,343 times in 1,780 papers; thus, a total of 322 keywords (5,195 appearances) were selected for the final analysis. The network analysis and network visualization tool used were NodeXL and PFnet, respectively. The keywords which appeared the most frequently were "Posttraumatic growth," followed by "Posttraumatic Stress Disease," "Cancer," and "Trauma." A total of 322 nodes have been reduced to 175 nodes and divided into a total of five groups. The five groups were "Posttraumatic Growth in Cancer, Chronic/Serious Illness, and Disability," "Posttraumatic Growth-related Psychological Variables and Psychotherapy," "Posttraumatic Growth in the Context of Death," "Cognitive Mechanisms of Posttraumatic Growth," and "Vicarious Posttraumatic Growth." This study provides a systematic overview on the knowledge structure of posttraumatic growth by quantitatively network analysis.

• Pediatric Infection and Vaccine
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• v.29 no.3
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• pp.166-172
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• 2022

Blau syndrome is a systemic autoinflammatory disease presenting with non-caseating granulomatous dermatitis, chronic uveitis, and arthritis. It is caused by a gain-of-function variant of the nucleotide-binding oligomerization domain protein 2 gene, which leads to the overactivation of inflammatory cytokines and eventually causes autoinflammation. Since the symptoms of Blau syndrome are nonspecific and usually do not appear simultaneously, it is challenging to differentiate Blau syndrome from other inflammatory disorders. This is a case report of a 13-month-old boy who had suffered from recurrent skin rash and fever. The patient was previously misdiagnosed as refractory Kawasaki disease twice and was treated with intravenous immunoglobulin and systemic glucocorticoid, which only resulted in transient improvement of the symptoms. He was eventually diagnosed with Blau syndrome.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.147-149
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• 2022

This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

• Membrane Journal
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• v.32 no.1
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• pp.33-42
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• 2022

Growing industrialization leads to severe water pollution. Organic effluents from pharmaceuticals and textile industries released in wastewater adversely affect the environment and human health. Presence of antibiotics used for antibacterial treatment in wastewater leads to the growth of drug resistance bacteria, which is very harmful for human being. Various small organic molecules are used for the preparation of organic dye molecules in the textile industries. These molecules hardly degrade, which is present in the wastewater effluents from printing and dyeing industries. In order to address these problems, photoactive catalyst is embedded in the membrane and wastewater are passed through it. Through this process, organic molecules are photodegraded and at the same time, the degraded compounds are separated by the membrane. Titanium dioxide (TiO₂) is a semiconductor which behave as excellent photocatalyst. Photocatalytic ability is enhanced by the making its composite with other transition metal oxide and incorporated into polymeric membrane. In this review, the degradation of dye and drug molecules by photocatalytic membrane are discussed.

• Design Convergence Study
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• v.17 no.3
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• pp.1-19
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• 2018

Hand rehabilitation training tools are used in hospitals and at home for patients and users who require recovery of disabled hands and improvement in overall hand function. However, existing training tools are not organized into a progressive system, and they lead to repeatability operations over a period of time. As a result, patients feel free and cannot be motivated by rehabilitation, and continuous rehabilitation training is difficult. Based on this argument, the study combines one of the elements of the game called the "Cat's cradle" to enable the user to feel achievement through play and to achieve natural rehabilitation through unconsciousness. After examining the characteristics of the tool, the user's environment, the relevance of the Cat's cradle game to the training tool and to the patient's continued rehabilitation was established. And design elements were derived through professional interviews. Later, design guidelines and prototypes have been created to complement the problems associated with guidelines and prototypes by conducting usability testing and design element assessment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.474-476
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• 2021

Glioblastoma is the most common brain malignancies arising from glial cells. Early diagnosis and treatment plan establishment are important, and cancer is diagnosed mainly through T1CE imaging through injection of a contrast agent. However, the risk of injection of gadolinium-based contrast agents is increasing recently. Region segmentation that marks cancer regions in medical images plays a key role in CAD systems, and deep neural network models for synthesizing new images are also being studied. In this study, we propose a model that simultaneously learns the generation of T1CE images and segmentation of cancer regions. The performance of the proposed model is evaluated using similarity measurements including mean square error and peak signal-to-noise ratio, and shows average result values of 21 and 39 dB.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.127-135
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• 2023

Accurate segmentation of histopathology whole slide images (WSIs) is a crucial task for disease diagnosis and treatment planning. However, conventional automated segmentation algorithms may not always be applicable to WSI segmentation due to their large size and variations in tissue appearance, staining, and imaging conditions. Recent advances in interactive segmentation, which combines human expertise with algorithms, have shown promise to improve efficiency and accuracy in WSI segmentation but also presented us with challenging issues. In this paper, we propose a novel interactive segmentation method, ZoomISEG, that leverages multi-resolution WSIs. We demonstrate the efficacy and performance of the proposed method via comparison with conventional single-scale methods and an ablation study. The results confirm that the proposed method can reduce human interaction while achieving accuracy comparable to that of the brute-force approach using the highest-resolution data.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.729-736
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• 2021

Multiple primary malignant neoplasms refer to two or more malignancies in an individual that are not related. We report a case of a 78-year-old male with concurrent breast mucinous carcinoma and extramammary lymphoma. The patient initially presented with palpable masses in the left breast and the right groin, which were pathologically confirmed after a surgical biopsy as breast mucinous carcinoma and diffuse large B-cell lymphoma, respectively. He underwent whole-body 18-fluorine deoxyglucose PET/CT before surgery, and an enhancing nodular lesion in the left lingual tonsil was found incidentally. It was later confirmed as a diffuse large B-cell lymphoma, a pathology of the same type as the right inguinal mass. Unspecified lymphadenopathies in breast cancer patients may easily be considered as metastatic lesions. However, this case suggests that lymphomas should be included in the differential diagnoses to avoid misdiagnosis and treatment delay, especially in older adult patients.

• Information Systems Review
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• v.19 no.2
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• pp.57-70
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• 2017

Researchers and industry managers highlight the emergence of mobile healthcare market given the rapid development of IT and the expansion of average life expectancy. Medical institutions, such as university hospitals, are aiming to achieve convenience and effectiveness of treatment by providing patient education through a mobile device. This study examines a case related to the development and usage of a mobile application based on Lean Canvas, namely, the Smart Explanation Service released by Samsung Medical Center. This application comprehensively analyzes the usage status of mobile application-based patient education and its application in clinical settings. This study also examines the level of satisfaction of patients and medical workers toward this application. The result of this study is expected to provide meaningful implication to medical institutions and related industries and enable them to create and offer prepare mobile healthcare services.