• Molecules and Cells
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• v.25 no.2
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• pp.242-246
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• 2008

To assess the role of $\alpha_{1G}$ T-type $Ca^{2+}$ channels in neuropathic pain after L5 spinal nerve ligation, we examined behavioral pain susceptibility in mice lacking $Ca_{V}3.1$ (${\alpha}_{1G}{^{-/-}}$), the gene encoding the pore-forming units of these channels. Reduced spontaneous pain responses and an increased threshold for paw withdrawal in response to mechanical stimulation were observed in these mice. The ${{\alpha}_{1G}}^{-/-}$ mice also showed attenuated thermal hyperalgesia in response to both low-(IR30) and high-intensity (IR60) infrared stimulation. Our results reveal the importance of ${\alpha}_{1G}$ T-type $Ca^{2+}$ channels in the development of neuropathic pain, and suggest that selective modulation of ${\alpha}_{1G}$ subtype channels may provide a novel approach to the treatment of allodynia and hyperalgesia.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.209-210
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• 2006

We have successfully termed brown colored patterns inside of a transparent borosilicate glass generally known as BK7, laying the focus of near infrared Ti: sapphire femtosecond laser beam in the bulk BK7 glass. It is important to keep the laser power well below the damage threshold of BK7 in forming the color center. Thanks to the low laser power, there was no laser induced mechanical damage such as cracks or threads in the color formed area. From the absorbance spectrum and its gaussian fitting, we found the band gap of BK7, 4.21eV, and three absorption edges.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.1-19
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• 1993

A simple bispectral threshold technique which reflects the temporal and spatial characteristics of the analysis area has been developed to classify the cloud type and estimate the cloud cover from GMS/S-VISSR(Stretched Visible and Infrared Spin Scan Radiometer) imagery. In this research, we divided the analysis area into land and sea to consider their different optical properties and used the same time observation data to exclude the solar zenith angle effects included in the raw data. Statistical clear sky radiance(CSRs) was constructed using maximum brightness temperature and minimum albedo from the S-VISSR imagery data during consecutive two weeks. The CSR used in the cloud anaysis was updated on the daily basis by using CSRs, the standard deviation of CSRs and present raw data to reflect the daily variation of temperature. Thresholds were applied to classify the cloud type and estimate the cloud cover from GMS/S-VISST imagery. We used a different thresholds according to the earth surface type and the thresholds were enough to resolve the spatial variation of brightness temperature and the noise in raw data. To classify the ambiguous pixels, we used the time series of 2-D histogram and local standard deviation, and the results showed a little improvements. Visual comparisons among the present research results, KMA's manual analysis and observed sea level charts showed a good agreement in quality.

• Physical Therapy Rehabilitation Science
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• v.10 no.3
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• pp.374-378
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• 2021

Objective: Bilateral movement training is an effective method for upper extremity rehabilitation of stroke. An approach to induce bilateral movement through functional electrical stimulation is attempted. The purpose of this study is to develop an EMG-triggered functional electrical stimulation device for upper extremity bilateral movement training in stroke patients and test its feasibility. Design: Feasibility and Pilot study design. Methods: We assessed muscle activation and kinematic data of the affected and unaffected upper extremities of a stroke patient during wrist flexion and extension with and without the device. Wireless EMG was used to evaluate muscle activity, and 12 3D infrared cameras were used to evaluate kinematic data. Results: We developed an EMG-triggered functional electrical stimulation device to enable bilateral arm training in stroke patients. A system for controlling functional electrical stimulation with signals received through a 2-channel EMG sensor was developed. The device consists of an EMG sensing unit, a functional electrical stimulation unit, and a control unit. There was asymmetry of movement between the two sides during wrist flexion and extension. With the device, the asymmetry was lowest at 60% of the threshold of the unaffected side. Conclusions: In this study, we developed an EMG-triggered FES device, and the pilot study result showed that the device reduces asymmetry.

• Current Applied Physics
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• v.18 no.12
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• pp.1546-1552
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• 2018

The polymer nanocomposite as a gate dielectric film was prepared via sol-gel method. The formation of crosslinked structure among nanofillers and polymer matrix was proved by Fourier transform infrared spectroscopy (FT-IR). Differential thermal analysis (DTA) results showed significant increase in the thermal stability of the nanocomposite with respect to that of pure polymer. The nanocomposite films deposited on the p- and n-type Si substrates formed very smooth surface with rms roughness of 0.045 and 0.058 nm respectively. Deconvoluted $Si_{2s}$ spectra revealed the domination of the Si-OH hydrogen bonds and Si-O-Si covalence bonds in the structure of the nanocomposite film deposited on the p- and n-type Si semiconductor layers respectively. The fabricated n-channel field-effect-transistor (FET) showed the low threshold voltage and leakage currents because of the stronger connection between the nanocomposite and n-type Si substrate. Whereas, dominated hydroxyl groups in the nanocomposite dielectric film deposited on the p-type Si substrate increased trap states in the interface, led to the drop of FET operation.

• Current Optics and Photonics
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• v.6 no.1
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• pp.92-103
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• 2022

The development of midinfrared (mid-IR) quantum cascade lasers (QCLs) has enabled rapid high-contrast measurement of the mid-IR spectra of biological tissues. Several studies have compared the differences between the mid-IR spectra of colon cancer and noncancerous colon tissues. Most mid-IR spectrum classification studies have been proposed as machine-learning-based algorithms, but this results in deviations depending on the initial data and threshold values. We aim to develop a process for classifying colon cancer and noncancerous colon tissues through a deep-learning-based convolutional-neural-network (CNN) model. First, we image the midinfrared spectrum for the CNN model, an image-based deep-learning (DL) algorithm. Then, it is trained with the CNN algorithm and the classification ratio is evaluated using the test data. When the tissue microarray (TMA) and routine pathological slide are tested, the ML-based support-vector-machine (SVM) model produces biased results, whereas we confirm that the CNN model classifies colon cancer and noncancerous colon tissues. These results demonstrate that the CNN model using midinfrared-spectrum images is effective at classifying colon cancer tissue and noncancerous colon tissue, and not only submillimeter-sized TMA but also routine colon cancer tissue samples a few tens of millimeters in size.

• Journal of the Korean earth science society
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• v.27 no.4
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• pp.450-463
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• 2006

Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.541-548
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• 2015

Objective: We introduce a hand gesture segmentation method using a wrist-worn wearable device which can recognize simple gestures of clenching and unclenching ones' fist. Background: There are many types of smart watches and fitness bands in the markets. And most of them already adopt a gesture interaction to provide ease of use. However, there are many cases in which the malfunction is difficult to distinguish between the user's gesture commands and user's daily life motion. It is needed to develop a simple and clear gesture segmentation method to improve the gesture interaction performance. Method: At first, we defined the gestures of making a fist (start of gesture command) and opening one's fist (end of gesture command) as segmentation gestures to distinguish a gesture. The gestures of clenching and unclenching one's fist are simple and intuitive. And we also designed a single gesture consisting of a set of making a fist, a command gesture, and opening one's fist in order. To detect segmentation gestures at the bottom of the wrist, we used a wrist strap on which an array of infrared sensors (emitters and receivers) were mounted. When a user takes gestures of making a fist and opening one's a fist, this changes the shape of the bottom of the wrist, and simultaneously changes the reflected amount of the infrared light detected by the receiver sensor. Results: An experiment was conducted in order to evaluate gesture segmentation performance. 12 participants took part in the experiment: 10 males, and 2 females with an average age of 38. The recognition rates of the segmentation gestures, clenching and unclenching one's fist, are 99.58% and 100%, respectively. Conclusion: Through the experiment, we have evaluated gesture segmentation performance and its usability. The experimental results show a potential for our suggested segmentation method in the future. Application: The results of this study can be used to develop guidelines to prevent injury in auto workers at mission assembly plants.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.471-482
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• 2016

This paper presents an extraction method for water body which uses block-based image partitioning and extension of water body boundaries to improve the performance of supervised classification for water body extraction. The Mahalanobis distance image is created by computing the spectral information of Normalized Difference Water Index (NDWI) and Near Infrared (NIR) band images over a training site within the water body in order to extract an initial water body area. To reduce the effect of noise contained in the Mahalanobis distance image, we apply mean curvature diffusion to the image, which controls diffusion coefficients based on connectivity strength between adjacent pixels and then extract the initial water body area. After partitioning the extracted water body image into the non-overlapping blocks of same size, we update the water body area using the information of water body belonging to water body boundaries. The update is performed repeatedly under the condition that the statistical distance between water body area belonging to water body boundaries and the training site is not greater than a threshold value. The accuracy assessment of the proposed algorithm was tested using KOMPSAT-2 images for the various block sizes between $11{\times}11$ and $19{\times}19$. The overall accuracy and Kappa coefficient of the algorithm varied from 99.47% to 99.53% and from 95.07% to 95.80%, respectively.