• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.40-48
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• 2009

Leading of the computer, IT technology has make great strides. As a information-industry-community was highly developed, user's needs to convenience about intelligence and humanization of interface is being increase today. Nowadays, researches with are related to BCI are progress put the application-technology development first in importance eliminating research about fountainhead technology with DB construction. These problems are due to a BCI-related research studies have not overcome the initial level, and not toward a systematic study. Brain wave are collected from subjects is a signal that the signal is appropriate and necessary in the experiment is difficult to distinguish. In addition, brain wave that it's not necessary to collect the experiment, serious eyes flicker, facial and body movements of an EMG and electrodes attached to the state, noise, vibration, etc. It is hard to collect accurate brain wave was caused by mixing disturbance wave in experiment on the environment. This movement, and the experiment of subject impact on the environment due to the mixing disturbance wave can cause that lowering cognitive and decline of efficiency when embodied BCI system. Therefore, in this paper, we propose an accurate and efficient brain-wave DB building system that more exactness and cognitive basis studies when embodied BCI system with brain-wave. For the minimize about brain wave DB with mixing disturbance, we propose a DB building method using an automatic control and prevent unnecessary action, put to use the subjects face tracking.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.3
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• pp.31-40
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• 2012

The irregularity of railway track affects not only the comfort of ride such as noise or vibration but also the safety of train operation. For this reason, it is an interesting research area to design a reliable and sustainable railway track system and to analyze the train movement mechanism based on systematic approaches considering reasons of track irregularity possible in a specific local environment. Irregularity data inspected by EM-120, an railway inspection system in Korea includes unavoidable incomplete and erratic information, so it is encountered lots of problem to analyse those data without appropriate pre-data-refining processes. In this research, for the efficient management and maintenance of railway system, progress rate of standard deviation of irregularity is quantified. During the computation, some important components of railways such as rail joint, ballast, roadbed, and fastener have been considered. Probabilistic distributions of irregularity growth with respect to time are computed to predict the remaining service life of railway track and to be adapted for the safety assessment.

• The Korean Journal of Nuclear Medicine Technology
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• v.24 no.1
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• pp.15-19
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• 2020

Purpose Generative Adversarial Network(GAN) is one of deep learning technologies. This is a way to create a real fake image after learning the real image. In this study, after acquiring artificial intelligence images through GAN, We were compared and evaluated with real scan time images. We want to see if these technologies are potentially useful. Materials and Methods 30 patients who underwent ¹⁸F-FDG Brain PET/CT scanning at Severance Hospital, were acquired in 15-minute List mode and reconstructed into 1,2,3,4,5 and 15minute images, respectively. 25 out of 30 patients were used as learning images for learning of GAN and 5 patients used as verification images for confirming the learning model. The program was implemented using the Python and Tensorflow frameworks. After learning using the Pix2Pix model of GAN technology, this learning model generated artificial intelligence images. The artificial intelligence image generated in this way were evaluated as Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR), and Structural Similarity Index(SSIM) with real scan time image. Results The trained model was evaluated with the verification image. As a result, The 15-minute image created by the 5-minute image rather than 1-minute after the start of the scan showed a smaller MSE, and the PSNR and SSIM increased. Conclusion Through this study, it was confirmed that AI imaging technology is applicable. In the future, if these artificial intelligence imaging technologies are applied to nuclear medicine imaging, it will be possible to acquire images even with a short scan time, which can be expected to reduce artifacts caused by patient movement and increase the efficiency of the scanning room.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.63-70
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• 2018

Biomedical signal measurement technology using images has been developed, and researches on respiration signal measurement technology for maintaining life have been continuously carried out. The existing technology measured respiratory signals through a thermal imaging camera that measures heat emitted from a person's body. In addition, research was conducted to measure respiration rate by analyzing human chest movement in real time. However, the image processing using the infrared thermal image may be difficult to detect the respiratory organ due to the external environmental factors (temperature change, noise, etc.), and thus the accuracy of the measurement of the respiration rate is low.In this study, the images were acquired using visible light and infrared thermal camera to enhance the area of the respiratory tract. Then, based on the two images, features of the respiratory tract region are extracted through processes such as face recognition and image matching. The pattern of the respiratory signal is classified through the k-nearest neighbor classifier, which is one of the statistical classification methods. The respiration rate was calculated according to the characteristics of the classified patterns and the possibility of breathing rate measurement was verified by analyzing the measured respiration rate with the actual respiration rate.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.867-874
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• 2023

Recently, many problems are occurring in the bee ecosystem due to rapid climate change. The decline in the bee population and changes in the flowering period are having a huge impact on the harvest of bee-keepers. Since it is impossible to continuously observe the beehives in the hive with the naked eye, most people rely on knowledge based on experience about the state of the hive.Therefore, interest is focused on smart beekeeping incorporating IoT technology. In particular, with regard to swarming, which is one of the most important parts of beekeeping, we know empirically that the swarming time can be determined by the sound of the queen bee, but there is no way to systematically analyze this with data.You may think that it can be done by simply recording the sound of the queen bee and analyzing it, but it does not solve various problems such as various noise issues around the hive and the inability to continuously record.In this study, we developed a system that records queen bee sounds in a real-time cloud system and analyzes sound patterns.After receiving real-time analog sound from the hive through multiple channels and converting it to digital, a sound pattern that was continuously output in the queen bee sound frequency band was discovered. By accessing the cloud system, you can monitor sounds around the hive, temperature/humidity inside the hive, weight, and internal movement data.The system developed in this study made it possible to analyze the sound patterns of the queen bee and learn about the situation inside the hive. Through this, it will be possible to predict the swarming period of bees or provide information to control the swarming period.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.5 s.108
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• pp.461-475
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• 2006

In this paper, it is described about the tri-band mobile antenna system design to provide broadband multimedia and direct broadcasting services using goo-stationary Koreasat 3, simultaneously operated in Ka/K/Ku band. The radiating part of the antenna system with a fan beam characteristic in the elevation plane is composed of the quasi-offset dual shaped reflector and the tri-band feeder. The tri-band feeder is also composed of the Ka/K dual band feeder with the protruding dielectric rod, the circular polarizer, the ortho-mode transducer and the circular-polarized Ku band feed array. Especially, the Ka/K dual band circular polarizer was realized firstly using the comb-type structure. For fast satellite-tracking on the movement, the Ku band feed array has the structure of the $2{\times}2$ active phased array which can make electrical beams. And, the circular-polarized characteristic in the feed array was improved by $90^{\circ}$ rotating arrangement of four radiating elements polarized circularly by a $90^{\circ}$ hybrid coupler, respectively. Four beam forming channels to make electrical beams at Ku band are divided into the main beam channel and the tracking beam channel in the output, and noise temperature characteristics of each channel were analyzed on the basis of the contributions of internal sub_units. From the fabricated antenna system, the output power at $P_{1dBc}$ of Ka_Tx channel was measured more than 34.1 dBm and the measured noise figures of K/Ku_Rx channels were less than 2.4 dB and 1.5 dB, respectively, over the operating band. The radiation patterns with co- and cross-polarization in the tri-band were measured using a near-field measurement in the anechoic chamber. Especially, Ku radiation patterns were measured after correcting each initial phase of active channels with partial radiation patterns obtained from the independent excitation of each channel. The antenna gains measured in Ka/K/Ku band of the antenna system were more than 39.6 dBi, 37.5 dBi, 29.6 dBi, respectively. And, the antenna system showed good system performances such as Ka_Tx EIRP more than 43.7 dBW and K/Ku_Rx G/T more than 13.2 dB/K and 7.12 dB/K, respectively.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.18 no.2
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• pp.122-128
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• 2007

This study aims to analyze the voices of the patients with voice disorders including vocal fold paralysis, vocal fold cyst and vocal nodule/polyp in the aspect of acoustic phonetics. This study intends to collect subsidiary acoustic data in order to make a speech treatment and an standardization of vocal disorders. Subjects and Methods: The subjects of this study were 64 adult patients who underwent indirect laryngoscopy and laryngostroboscopy, and were diagnosed as vocal fold paralysis, vocal fold cyst or vocal nodule/polyp. Experimental group consisted of 20 patients who were diagnosed as vocal fold paralysis, 21 patients who were diagnosed as vocal fold cyst and had the average age of 42.0 $({\pm}10.03)$ ; and 23 patients who were diagnosed as vocal nodule/polyp and had the average age of 40.9 $({\pm}13.75)$. For the methodology of this study, the patients listed above were asked to sit in a comfortable position at intervals of 10cm apart from the patient's mouth and a microphone, and subsequently to phonate a vowel sound /e/ for the maximum phonation time with natural tone and vocal volume then the sound was directly inputted on a computer. During recording, sampling rate was set to 44,100Hz and the 1-second area corresponding to stable zone except the first and the last stage of waveform of the vowel sound /e/ vocalized by the individual patients was analyzed. Results: First, there was no statistically significant difference in jitter and shimmer between vocal fold paralysis and vocal fold cyst, while there was highly statistically significant difference in them between vocal fold paralysis and vocal nodule/polyp. Second, looking into the mean values obtained from NNE, HNR and SNR results associated with noise ratio, the disease showing the most abnormal characteristics was vocal fold paralysis, followed by cyst and nodule/polyp in order. For NNE, there was statistically significant difference between vocal nodule/polyp, and cyst or paralysis. In other words, it was found that the NNE of vocal nodule/polyp was weaker than that of cyst or paralysis. Similarly, HNR and SNR also showed the same characteristics; there was statistically significant difference between vocal fold paralysis and vocal fold cyst or nodule/polyp, and HNR and SNR values of vocal fold paralysis were lower than those of vocal fold cyst or nodule/polyp. Conclusion: For vocal fold paralysis, the abnormal values of acoustic parameters associated with frequency, amplitude and noise ratio were statistically significantly higher than those of vocal fold cyst and nodule/polyp. This finding suggests that the voices of the patients with vocal fold paralysis are the most severely injured due to less stability of vocal fold movement, asymmetry and incomplete glottic closure. In addition, there was no statistically significant difference in the acoustic parameters of tremor among vocal fold paralysis, vocal fold cyst and vocal nodule/polyp. Further studies need to ascertain reasonable acoustic parameters with various vocal disorders as well as to clarify the correlation between acoustics-based objective tools and subjective evaluations.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.249-261
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• 2020

Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.

• Investigative Magnetic Resonance Imaging
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• v.1 no.1
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• pp.109-113
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• 1997

Purpose: To evaluate the differences of functional imaging patterns between conventional spoiled gradient echo (SPGR) and echo planar imaging (EPI) methods in cerebral motor cortex activation. Materials and Methods: Functional MR imaging of cerebral motor cortex activation was examined on a 1.5T MR unit with SPGR (TRfrE/flip angle=50ms/4Oms/$30^{\circ}$, FOV=300mm, matrix $size=256{\times}256$, slice thickness=5mm) and an interleaved single shot gradient echo EPI (TRfrE/flip angle = 3000ms/40ms/$90^{\circ}$, FOV=300mm, matrix $size=128{\times}128$, slice thickness=5mm) techniques in five male healthy volunteers. A total of 160 images in one slice and 960 images in 6 slices were obtained with SPGR and EPI, respectively. A right finger movement was accomplished with a paradigm of an 8 activation/ 8 rest periods. The cross-correlation was used for a statistical mapping algorithm. We evaluated any differences of the time series and the signal intensity changes between the rest and activation periods obtained with two techniques. Also, the locations and areas of the activation sites were compared between two techniques. Results: The activation sites in the motor cortex were accurately localized with both methods. In the signal intensity changes between the rest and activation periods at the activation regions, no significant differences were found between EPI and SPGR. Signal to noise ratio (SNR) of the time series data was higher in EPI than in SPGR by two folds. Also, larger pixels were distributed over small p-values at the activation sites in EPI. Conclusions: Good quality functional MR imaging of the cerebral motor cortex activation could be obtained with both SPGR and EPI. However, EPI is preferable because it provides more precise information on hemodynamics related to neural activities than SPGR due to high sensitivity.