• The Journal of Korean Academy of Sensory Integration
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• v.8 no.1
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• pp.41-49
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• 2010

Objective : Multisensory integration (MSI) is the essential process to use diverse sensory information for cognitive task or execution of motor action. Especially, visual and somatosensory integration is critical for motor behavior and coordination. This study was designed to explain spatial and temporal characteristics of visual and somatosensory integration by neurophysiological research method that identifies the time course and brain location of the SI process. Methods : Electroencephalography (EEG) and event-related potential (ERP) is used in this study in order to observe neural activities when integrating visual and tactile input. We calculate the linear summation (SUM) of visual-related potentials (VEPs) and somatosensory-related potentials (SEPs), and compared the SUM with simultaneously presented visual-tactile ERPs(SIM) Results : There were significant differences between the SIM and SUM in later time epochs (about 200-300ms) at contralateral somatosensory areas (C4) and occipital cortices (O1&O2). The amplitude of the SIM was mathematically larger than the summed signals, implying that the integration made some extra neural activities. Conclusion : This study provides some empirical neural evidence of that multisensory integration is more powerful than just combing two unisensory inputs in the brain and ERP data reveals neural signature relating to multisensory integrative process. Since this study is preliminary pilot study, larger population and criteria are needed for level of the significance. Further study is recommended to consider issues including effect of internally-driven attention and laterality of interaction to make the evidence by this study solid.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.115-124
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• 2017

The objective of study was to investigate the optimal echo phase for mouse brain enhancement scan using fast low angle shot (FLASH) sequence of 9.4T magnetic resonance imaging (MRI). For quantification based on this method, an MR phantom experiment and clinical research were done. The phantom experiment was conducted by fabricating three phantoms with different molar concentration of gadolinium to create changes in echo phase of 9.4T FLASH sequence used in mouse brain scans. In the phantom experiment, SSI was 25~27 [arbitrary units, a.u.] in each of 33 phases from $6{\pi}$ to $28{\pi}$, while RSP was 30~100 mmol. MPSI was 47~52 [a.u], while MPP, where MPSI is seen, was 0.8~9 mmol. EPMS was 80.8~108.0%, while ASIMP was formed between 21.1 and 31.8 [a.u]. In the clinical research, Finally, the occurrence rate of artifact that expressed -1 nd +1. The present study was able to quantify the degree of enhancement at FLASH sequence of 9.4T MRI, as well as identify the optimal echo phase during mouse brain enhancement scan.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2185-2193
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• 2016

Background: The pathogenesis of sporadic colorectal cancer (CRC) is influenced by the patient genetic background and environmental factors. Based on prior understanding, these are classified in two major pathways of genetic instability. Microsatellite instability (MSI) and CPG island methylator phenotype (CIMP) are categorized as features of the hypermethylated prototype, and chromosomal instability (CIN) is known to be indicative of the non-hypermethylated category. Secreted frizzled related protein 2 (SFRP2), APC1A in WNT signaling pathway and the DNA repair gene, O6-methylguanine-DNA methyltransferase (MGMT), are frequently hypermethylated in colorectal cancer. Detection of methylated DNA as a biomarker by easy and inexpensive methods might improve the quality of life of patients with CRC via early detection of cancer or a precancerous condition. Aim: To evaluate the rate of SFRP2 and MGMT hypermethylation in both polyp tissue and serum of patients in south Iran as compared with matched control normal population corresponding samples. Materials and Methods: Methylation-specific PCR was used to detect hypermethylation in DNA extracted from 48 polypoid tissue samples and 25 healthy individuals. Results: Of total polyp samples, 89.5% had at least one promoter gene hypermethylation. The most frequent methylated locus was SFRP2 followed by MGMT-B (81.2 and 66.6 percent respectively). Serologic detection of hypermethylation was 95% sensitive as compared with polyp tissue. No hypermethylation was detected in normal tissue and serum and its detection in patients with polyps, especially of serrated type, was specific. Conclusions: Serologic investigation for detection of MGMT-B, SFRP2 hypermethylation could facilitate prioritization of high risk patients for colonoscopic polyp detection and excision.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.559-566
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• 2021

It is necessary to quickly detect and respond to ship accidents that occur continuously due to the influence of the recently increased maritime traffic. For this purpose, ship detection research is being actively conducted based on satellite images that can be monitored in real time over a wide area. However, there is a possibility that the wake may be falsely detected as a ship because the wake removal is not performed in previous studies that performed ship detection using spectral characteristics. Therefore, in this study, ship detection was performed using SDI (Ship Detection Index) based on the Sentinel-2A satellite image, and the wake was removed by utilizing the difference in the spectral characteristics of the ship and the wake. Probability of detection (POD) and false alarm rate (FAR) indices were used to verify the accuracy of the ship detection algorithm in this study. As a result of the verification, POD was similar and FAR was improved by 6.4% compared to the result of applying only SDI.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.251-263
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• 2019

Sentinel-2 Multi Spectral Instrument(MSI) launched by the European Space Agency (ESA) offered high spatial resolution optical products, enhanced temporal revisit of five days, and 13 spectral bands in the visible, near infrared and shortwave infrared wavelengths similar to Landsat mission. Landsat satellite imagery has been applied to various previous studies, but Sentinel-2 optical satellite imagery has not been widely used. Currently, for global coverage, Sentinel-2 products are systematically processed and distributed to Level-1C (L1C) products which contain the Top-of-Atmosphere (TOA) reflectance. Furthermore, ESA plans a systematic global production of Level-2A(L2A) product including the atmospheric corrected Bottom-of-Atmosphere (BOA) reflectance considered the aerosol optical thickness and the water vapor content. Therefore, the Sentinel-2 L2A products are expected to enhance the reliability of image quality for overall coverage in the Sentinel-2 mission with enhanced spatial,spectral, and temporal resolution. The purpose of this work is a quantitative comparison Sentinel-2 L2A products and fully simulated image to evaluate the applicability of the Sentinel-2 dataset in cultivated land growing various kinds of crops in Korea. Reference image of Sentinel-2 L2A data was simulated by airborne hyperspectral data acquired from AISA Fenix sensor. The simulation imagery was compared with the reflectance of L1C TOA and that of L2A BOA data. The result of quantitative comparison shows that, for the atmospherically corrected L2A reflectance, the decrease in RMSE and the increase in correlation coefficient were found at the visible band and vegetation indices to be significant.