• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.69-76
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• 2019

This study aimed to investigate the effects of vocal aerobic treatment (VAT) on the improvement of voice in patients with voice disorders. Twenty patients (13 males, 7 females) were diagnosed with voice disorders on the basis of videostroboscopy and voice evaluations. Acoustic evaluation was performed with the Multidimensional voice program (MDVP) and Voice Range Profile (VRP) of Computerized Speech Lab (CSL), and aerodynamic evaluation with PAS (Phonatory Aerodynamic System). The changes in F0, Jitter, Shimmer, and NHR before and after treatment were measured by MDVP. F0 range and Energy range were measured with VRP before and after treatment, and the changes in Expiratory Volume (FVC), Phonation Time (PHOT), Mean Expiratory Airflow (MEAF), Mean Peak Air Pressure (MPAP), and Aerodynamic Efficiency (AEFF) with PAS. Videostroboscopy was performed to evaluate the regularity, symmetry, mucosal wave, and amplitude changes of both vocal cords before and after treatment. Voice therapy was performed once a week for each patient using the VAT program in a holistic voice therapy approach. The average number of treatments per patient was 6.5. In the MDVP, Jitter, Shimmer, and NHR showed statistically significant decreases (p < .001, p < .01, p < .05). VRP results showed that Hz and semitones in the frequency range improved significantly after treatment (p < .01, p < .05), as did PAS, FVC, and PHOT (p < .01, p < .001). The results for videostroboscopy, functional voice disorder, laryngopharyngeal reflux, and benign vocal fold lesions were normal. Thus, the VAT program was found to be effective in improving the acoustic and aerodynamic aspects of the voice of patients with voice disorders. In future studies, the effect of VAT on the same group of voice disorders should be studied. It is also necessary to investigate subjective voice improvement and objective voice improvement. Furthermore, it is necessary to examine the effects of VAT in professional voice users.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.109-120
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• 2023

The High-Frequency Radar (HFR) is an equipment designed to measure real-time surface ocean currents in broad maritime areas.It emits radio waves at a specific frequency (HF) towards the sea surface and analyzes the backscattered waves to measure surface current vectors (Crombie, 1955; Barrick, 1972).The Seasonde HF Radar from Codar, utilized in this study, determines the speed and location of radial currents by analyzing the Bragg peak intensity of transmitted and received waves from an omnidirectional antenna and employing the Multiple Signal Classification (MUSIC) algorithm. The generated currents are initially considered ideal patterns without taking into account the characteristics of the observed electromagnetic wave propagation environment. To correct this, Antenna Pattern Measurement (APM) is performed, measuring the strength of signals at various positions received by the antenna and calculating the corrected measured vector to radial currents.The APM principle involves modifying the position and phase information of the currents based on the measured signal strength at each location. Typically, experiments are conducted by installing an antenna on a ship (Kim et al., 2022). However, using a ship introduces various environmental constraints, such as weather conditions and maritime situations. To reduce dependence on maritime conditions and enhance economic efficiency, this study explores the possibility of using unmanned aerial vehicles (drones) for APM. The research conducted APM experiments using a high-frequency radar installed at Dangsa Lighthouse in Dangsa-ri, Wando County, Jeollanam-do. The study compared and analyzed the results of APM experiments using ships and drones, utilizing the calculated radial currents and surface current fields obtained from each experiment.

• Sleep Medicine and Psychophysiology
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• v.3 no.2
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• pp.32-42
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• 1996

Objectives : Upper airway resistance syndrome(UARS) is a sleep-related breathing disorder characterized by abnormal negative intrathoracic pressure during sleep. Abnormally increased negative intrathoracic pressure results in microarousal and sleep fragmentation which underlay UARS-associated complaints of daytime fatigue and sleepiness. Although daytime dysfunction in patients with UARS is comparable to that of sleep apnea syndrome, UARS has been relatively unnoticed in clinical setting. That is why UARS is apt to be excluded in diagnosing of sleep-related breathing disorders since its respiratory disturbance index and arterial oxygen saturation are within normal limits. The current study presents a summary of clinical and polysomnographic characteristics found in patients with UARS. The present study aims (1) to explore characteristics of patients diagnosed with UARS, (2) to characterize the polysomnographic findings of UARS patients, and (3) to enhance the understanding of UARS through those clinical and laboratory characteristics. Methods : This was a retrospective study of 20 UARS patients (male 15, female 5) and 30 obstructive sleep apnea (OSA) patients (male 21, female 9) at the Stanford Sleep Disorders Clinic. We diagnosed patients as having UARS when they met critenia, RDI < 5 characteristic findings of an elevated esophageal pressure($<-10\;cmH_2O$), frequent arousals secondary to an elevated esophageal pressure, and symptoms of daytime fatigue and sleepiness. We used polysomnographic value, which is standardized by Williams et al(1974), as normal control. Statiotical test were done with student t-tests. Results : (1) Mean age of UARS was $41.0\;{\pm}\;14.8$ years and OSA was $50.9\;{\pm}\;12.0$ years. UARS subject was significantly younger than OSA subject (p<0.05). (2) The total score of Epworth Sleepiness Scale (ESS) was UARS $9.7\;{\pm}\;6.3$ and OSAS $11.2\;{\pm}\;6.3$. There was no significant difference between two groups. (3) The mean body mass index was UARS $28.1\;{\pm}\;5.7\;kg/m^2$ and OSAS $32.9\;{\pm}\;7.0\;kg/m^2$. UARS had significantly lower meen body man index than OSAS subjects (p<0.05). (4) The polysomnographic parameters of UARS were not significantly different from those of OSA except RDI(p<0.001), $SaO_2$ (p<0.001) and slow wave sleep latency (p<0.05). (5) Compared with normal control, Total sleep time in UARS subjects was significantly shorter (p<0.001), sleep efficiency index was significantly lower (p<0.001), total awakening percentage was significantly higher (p<0.001), and sleep stage 1 (p<0.001) were significantly higher. (6) OSA patients showed poor sleep quality and distinct abnormal sleep architectures compared with normal control. Conclusions : Conclusions from the above results are as follows : (1) UARS patients were younger and had lower body mass index when umpared with OSA patients. (2) The quality of sleep and sleep architectures of the UARS and OSA patients are significantly different from those of normal control. (3) ESS scores and awakening frequencies of UARS are similar with those of OSA, suggesting that daytime dysfunction of UARS patients may be comparable to those of OSA patients. (4) The RDI and the $SaO_2$ which are important indicators in diagnosing sleep-related breathing disorders, of UARS subjects are close to normal value. (5) According to the the above results, we unclude that despite the absence of $SaO_2$ drops and the absence of an elevated number of apnea and hypopnea, subjects developed clinical complaints which were associated with laborious breathing, elevated Pes nadir, and frequently snoring. (6) Accordingly, we suggest including LIARS in the differential diagnosis list when sleep related breathing disorder is suspected clinically and overnight polysomnographic findings except snoring and frequent microarousal are within normal limits.