• Journal of Biomedical Engineering Research
• /
• v.25 no.1
• /
• pp.11-19
• /
• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.4 no.4
• /
• pp.400-404
• /
• 1999

The conventional mercury delay method to measure compressional wave velocity of unconsolidated sediment is inconvenient because the signal must be analyzed on the oscilloscope and the mercury column has to be calibrated between measurements. We developed an automated compressional wave velocity measurement technique by connecting an oscilloscope and a PC with a GPIB (General Purpose Interface Bus) card. The GPIB card buses signals from the oscilloscope to the PC where the signal from a sample is analyzed and compared to the input pulse thereby the compressional wave velocity of the sample is computed and recorded automatically. Differences between the mercury delay method and the automated measurement technique are negligible except the slightly greater velocity in the automated measurement technique. We concluded that the new technique can be used to measure the velocity for unconsolidated marine sediment. It also has an advantage to calculate sediment attenuation through the processing of waveform using the spectral ratio technique.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_1
• /
• pp.455-467
• /
• 2017

When performing target detection using hyperspectral imagery, a feature extraction process is necessary to solve the problem of redundancy of adjacent spectral bands and the problem of a large amount of calculation due to high dimensional data. This study proposes a new band selection method using the $L_{2,1}$-norm regression model to apply the feature selection technique in the machine learning field to the hyperspectral band selection. In order to analyze the performance of the proposed band selection technique, we collected the hyperspectral imagery and these were used to analyze the performance of target detection with band selection. The Adaptive Cosine Estimator (ACE) detection performance is maintained or improved when the number of bands is reduced from 164 to about 30 to 40 bands in the 350 nm to 2500 nm wavelength band. Experimental results show that the proposed band selection technique extracts bands that are effective for detection in hyperspectral images and can reduce the size of the data without reducing the performance, which can help improve the processing speed of real-time target detection system in the future.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_2
• /
• pp.1061-1073
• /
• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2006.05a
• /
• pp.462-466
• /
• 2006

Close-to-nature stream evaluation is one of the processing to make the streams over in order to keep them natural. It is integral to evaluate and make an accurate analysis of them on the purpose of maintaining streams healthy. For many instances, there are, stream organization evaluation for restoration by German government, evaluation for ecosystem protection in natural preserves by New Zealand government, and stream-view evaluation for restoration by Britain government so on. In case of the country there are analysis and evaluation of stream physical organization by Cho, Yong-hyun, Close-to-nature stream evaluation for restoration by Kim, Dong-chan, evaluation of stream properties in korea by Park, Bong-jin. Close-to-nature evaluation by Lim, Chan-uk, that is advanced version of Park, Bong-jin's, shows form of stream including waterway curve, sand bar, diversity of flow, river bed material, diversity of minor bed, minor bed bank protection works, bank protection material. It also does environment of stream including side of minor bed vegetation, width of surface of the water/width of the river etc.. By the way, this evaluation does not have free access to apply those details above in the field, it often happens that you get various outcome from the one spot. so you must need more realistic testing method to obtain more accurate data. Remote sensing method is highly recommended because this is very useful for collecting realistic data of vegetation index. what is more, it can not only scan even the minimum area within its resolving power but also do obtain data anytime. Vegetation index indicates Ratio vegetation index, Normalized difference vegetation index, Soil adjusted vegetation index, Atmospherically resistant vegetation index etc.. The research is focusing on Cheokgwa stream which is the branch of Taehwa river and shows 19 sectioned Close-to-nature stream performed according to the method by Lim, chan-uk. Besides let you know vegetation index came from image data of satellite landsat 7 with the variation of buffering area, of the day 9. may. 2003. Of all, the outcome 0.758 at 200m buffer-zone of NDVI was the best we have got so far.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1522-1522
• /
• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Journal of Astronomy and Space Sciences
• /
• v.26 no.4
• /
• pp.567-588
• /
• 2009

Korea-Japan Joint VLBI Correlator (KJJVC) is being developed by collaborating KASI (Korea Astronomy and Space Science Institute), Korea, and NAOJ(National Observatory of Japan), Japan. In early 2010, KJJVC will work in normal operation. In this study, we developed the software correlator which is based on VCS (VLBI Correlation Subsystem) hardware specification as the core component of KJJVC. The main specification of software correlator is 8 Gbps, 8192 output channels, and 262,144-points FFT (Fast Fourier Transform) function same as VCS. And the functional algorithm which is same as specification of VCS and arithmetic register are adopted in this software correlator. To verify the performance of developed software correlator, the correlation experiments were carried out using the spectral line and continuum sources which were observed by VERA (VLBI Exploration of Radio Astrometry), NAOJ. And the experimental results were compared to the output of Mitaka FX correlator by referring spectrum shape, phase rate, and fringe detection and so on. Through the experimental results, we confirmed that the correlation results of software correlator are the same as Mitaka FX correlator and verified the effectiveness of it. In future, we expect that the developed software correlator will be the possible software correlator of KVN (Korean VLBI Network) with KJJVC by introducing the correlation post-processing and modifying the user interface as like GUI (Graphic User Interface).

• Geophysics and Geophysical Exploration
• /
• v.19 no.1
• /
• pp.11-19
• /
• 2016

Two representative residual static methods of traveltime decomposition and stack-power maximization are discussed in terms of application to land seismic data. For the model data with synthetic shot/receiver statics (time shift) applied and random noises added, continuities of reflection event are much improved by stack-power maximization method, resulting the derived time-shifts approximately equal to the synthetic statics. Optimal parameters (maximum allowable shift, correlation window, iteration number) for residual statics are effectively chosen with diagnostic displays of CSP (common shot point) stack and CRP (common receiver point) stack as well as CMP gather. In addition to removal of long-wavelength time shift by refraction statics, prior to residual statics, processing steps of f-k filter, predictive deconvolution and time variant spectral whitening are employed to attenuate noises and thereby to minimize the error during the correlation process. The reflectors including horizontal layer of reservoir are more clearly shown in the variable-density section through repicking the velocities after residual statics and inverse NMO correction.

• Korean Journal of Soil Science and Fertilizer
• /
• v.37 no.4
• /
• pp.259-265
• /
• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_4
• /
• pp.1327-1339
• /
• 2019

Surface reflectance obtained by absolute atmospheric correction from satellite images is useful for scientific land applications and analysis ready data (ARD). For Landsat and Sentinel-2 images, many types of radiometric processing methods have been developed, and these images are supported by most commercial and open-source software. However, in the case of KOMPSAT 3/3A images, there are currently no tools or open source resources for obtaining the reflectance at the top-of-atmosphere (TOA) and top-of-canopy (TOC). In this study, the atmospheric correction module of KOMPSAT 3/3A images is newly implemented to the optical calibration algorithm supported in the Orfeo ToolBox (OTB), a remote sensing open-source tool. This module contains the sensor model and spectral response data of KOMPSAT 3A. Aerosol measurement properties, such as AERONET data, can be used to generate TOC reflectance image. Using this module, an experiment was conducted, and the reflection products for TOA and TOC with and without AERONET data were obtained. This approach can be used for building the ARD database for surface reflection by absolute atmospheric correction derived from KOMPSAT 3/3A satellite images.