• Journal of Music and Human Behavior
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• v.4 no.1
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• pp.31-46
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• 2007

The purpose of the study was to improve the efficiency of Breath & Forced Vital Capacity(FVC) of Stroke Patients Using Record Playing Focused on Breath Training. The Training of Forced Vital Capacity(FVC) is focused on trunk muscles reinforce for Breathing. So the study tried to play Recorder for reinforcing FVC. The play included the two parts. One was for solo play, the other was play in concert base on solo play using Korea country song, Arirang. The Recorder play used abdominal breath, Pursed-lip & Paced methods. The course of play included Long Tone, Staccato, Crescendo, Decrescendo and throughout the course we tried to improve the efficiency & Quantity of breathe. Experiment performed at Social welfare institute for the old. They played & checked FVC, $FEV_1$, $FEV_1/FVC$ before & after breathe 19 times for 6 weeks using Spirovit SP-1, Schiller. After experiment we performed statical process(p<0.05) using statical Package software. The findings were as follows: Analysis for Experiment showed the numerical Value of increasing Of FVC, $FEV_1$, $FEV_1/FVC$. Increasing Percentage of Measured/Predicted FVC, $FEV_1$ (or calculated based on theory) ration was 25%, 13% and Quantity of FVC, $FEV_1$ 35%, 40%. Also $FEV_1/FVC$ Ratio(showed efficiency of breathe) raised 13%. And experiment data was confirmed by statical process. The experiment data was valuable under p<0.05. In Conclusion we think the results of experiment showed the efficiency of Music therapy for Breathe(FVC, $FEV_1$, $FEV_1/FVC$) reinforce.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.393-400
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• 2023

Acetone, a metabolite detected from the exhaled breath of people doing a diet, can be used for non-invasive monitoring of diet efficiency. Thus, gas sensors with rapid response and recovery characteristics to acetone need to be developed. Herein, we report ultrafast acetone sensors using Ce-doped In₂O₃ nanoparticles prepared by the one-pot microwave-assisted hydrothermal method. The pure In₂O₃ sensor shows a high response and fast response time (τ_res = 6 s) upon exposure to 2 ppm acetone at 300 ℃, while exhibiting a relatively sluggish recovery speed (τ_recov = 1129 s). When 20 wt% Ce is doped, the τ_recov of the sensor significantly decreased to 45 s withholding the fast-responding characteristic (τ_res = 6 s). In addition, the acetone response (resistance ratio, S) of the sensor is as high as 5.8, sufficiently high to detect breath acetone. Moreover, the sensor shows similar acetone sensing characteristics even under a highly humid condition (relative humidity of 60%) in terms of τ_res (6 s), τ_recov (47 s), and S (4.7), demonstrating its high potential in real applications. The excellent acetone sensing characteristics of Ce-doped In₂O₃ nanoparticles are discussed in terms of their size, composition, phase, and oxygen adsorption on the sensing surface.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.1-5
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• 2022

We presented a micro hemi-sphere structure flexible film to improve the external quantum efficiency (EQE) in OLEDs. The micro hemi-sphere flexible film was fabricated with breath figure (BF) method and replica process. At 45 mg/mL of concentration, the size of the hemi-spheres was approximately 6.2 ㎛ were obtained which are the most circular shape. So, it was possible to yield the best performance with an improvement of 33 % in the EQE and the widest viewing angle ranging from 0° to 70°. As a result, the hemi-sphere film's size and distribution seem to play important roles in enhancing the EQE in OLEDs. Furthermore, the flexible hemi-sphere film based on polymeric materials could offer an effective, large-scale, mass-produced product and a simple process and approach to achieve high efficiency in flexible OLEDs.

• ETRI Journal
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• v.37 no.4
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• pp.824-832
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• 2015

Heart sounds are the main obstacle in lung sound analysis. To tackle this obstacle, we propose a diagnosis algorithm that uses singular spectrum analysis (SSA) and frequency features of heart and lung sounds. In particular, we introduce a frequency coefficient that shows the frequency difference between heart and lung sounds. The proposed algorithm is applied to a synthetic mixture of heart and lung sounds. The results show that heart sounds can be extracted successfully and localizations for the first and second heart sounds are remarkably performed. An error analysis of the localization results shows that the proposed algorithm has fewer errors compared to the SSA method, which is one of the most powerful methods in the localization of heart sounds. The presented algorithm is also applied in the cases of recorded respiratory sounds from the chest walls of five healthy subjects. The efficiency of the algorithm in extracting heart sounds from the recorded breathing sounds is verified with power spectral density evaluations and listening. Most studies have used only normal respiratory sounds, whereas we additionally use abnormal breathing sounds to validate the strength of our achievements.

• Physical Therapy Rehabilitation Science
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• v.12 no.3
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• pp.251-258
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• 2023

Objective: The practice of breathing exercises involves altering the depth and frequency of respiration. Strengthening respiratory muscles plays a crucial role in maintaining overall health and well-being. The efficiency of the respiratory system affects not only physical activity but also various physiological processes including cardiovascular health, lung function, and cognitive abilities. The study evaluated the reliability of the developed device for inspiratory/expiratory training using pressure sensors and Bluetooth connectivity with a smartphone application. Design: Design & development research Methods: The research methodology involved connecting a custom-made respiratory sensor to an IMT-PEP BIC Breath device. Various pressure conditions were measured, and statistical analyses were performed to assess reliability and consistency. Results showed high Intraclass Coefficient Correlation (ICC) values for both inspiratory and expiratory pressures, indicating strong test-retest reliability. The device was designed for ease of use and wireless monitoring through a smartphone app. Results: This study conducted at expiratory pressure confirmed the proper operation of the IMT/PEP breathing trainer at the specified pressure setting in the product. The pressure sensor demonstrated high test-retest reliability with an ICC value of 0.999 for both expiratory and inspiratory pressure measurements. Conclusions: The developed respiratory training device measured and monitored inspiratory and expiratory pressures, demonstrating its reliability for respiratory training. The system could be utilized to record training frequency and intensity, providing potential benefits for patients requiring respiratory interventions. Further research is needed to assess the full potential of the device in diverse populations and applications.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.37-42
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• 2008

This study is focused on the numerical predictions for different smoke-control ventilation modes for the subway fire. Smoke-control ventilation mode in the domestic platform is that exhausting for the smoke detected zones while supplying air or stopping any ventilation for other zones in the platform. Three cases of smoke control ventilation modes are considered. First and second case are present running smoke control mode in Korea. The third is that smoke-control ventilation fans equipped in the platform are operated in first 4 minute(platform evacuation time, NFPA130) since then the fans equipped in the platform are stopped and the fans equipped in the tunnels are operated. Distributions of heat, carbon monoxide and visible range are compared at a height of 1.7m(passenger breath/sight height) above the platform. The numerical results show that air supply fan operation in the platform causes the smoke disturbance and a rapid spread of the smoke. The switch-operation with fans in both the platform and tunnel are better than operation with only platform fans in smoke rejection efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.206-214
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• 2020

This study examined the correlation between the respiratory pattern change (RPC) and abdominal mobility (AM) according to the positive result of the subjective lumbar instability factor (SLIF) in people with chronic low back pain (CLBP). Thirty-six adults with CLBP participated in this study. Twenty-eight items of the SLIFs were examined, and the subjects were divided into three groups according to the positive response numbers (PRN). After the change lists were scored, three RPC scores [costo-diaphragmatic RPC (CDRPC), breath hold change (BHC), and total RPC (TRPC)] were obtained. The abdominal mobility (AM) was measured between the maximal inspiration and exhalation at the xiphoid (AM1) and the 10^th rib (AM2) level of the trunk. The results showed that the RPC score and AM were compared according to the positive response number of SLIF, and the relationship between them was analyzed. A positive correlation was observed between the SLIF positive response number and CDRPC score, BHC score, and total RPC score, and a negative correlation was observed between the SLIFs positive response number and AM1 and AM2. Based on the results of this study, the combination of SLIF positive responses can be a predictor of non-physiological respiratory pattern changes in people with CLBP. Clinically, this prediction is expected to help save time for screening and improve the efficiency of therapy.

• Radiation Oncology Journal
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• v.26 no.3
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• pp.181-188
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• 2008

Purpose: In order to enhance the efficiency of respiratory gated 4-dimensional radiation therapy for more regular and stable respiratory period and amplitude, a respiration training system was designed, and its efficacy was evaluated. Materials and Methods: The experiment was designed to measure the difference in respiration regularity following the use of a training system. A total of 11 subjects (9 volunteers and 2 patients) were included in the experiments. Three different breathing signals, including free breathing (free-breathing), guided breathing that followed training software (guided-breathing), and free breathing after the guided-breathing (post guided-breathing), were consecutively recorded in each subject. The peak-to-peak (PTP) period of the breathing signal, standard deviation (SD), peak-amplitude and its SD, area of the one cycle of the breathing wave form, and its root mean square (RMS) were measured and computed. Results: The temporal regularity was significantly improved in guided-breathing since the SD of breathing period reduced (free-breathing 0.568 vs guided-breathing 0.344, p=0.0013). The SD of the breathing period representing the post guided-breathing was also reduced, but the difference was not statistically significant (free-breathing 0.568 vs. guided-breathing 0.512, p=ns). Also the SD of measured amplitude was reduced in guided-breathing (free-breathing 1.317 vs. guided-breathing 1.068, p=0.187), although not significant. This indicated that the tidal volume for each breath was kept more even in guided-breathing compared to free-breathing. There was no change in breathing pattern between free-breathing and guided-breathing. The average area of breathing wave form and its RMS in postguided-breathing, however, was reduced by 7% and 5.9%, respectively. Conclusion: The guided-breathing was more stable and regular than the other forms of breathing data. Therefore, the developed respiratory training system was effective in improving the temporal regularity and maintaining a more even tidal volume.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.