Objective: Computed tomography (CT) is an established method for the diagnosis, staging, and treatment of multiple myeloma. Here, we investigated the potential of photon-counting detector computed tomography (PCD-CT) in terms of image quality, diagnostic confidence, and radiation dose compared with energy-integrating detector CT (EID-CT). Materials and Methods: In this prospective study, patients with known multiple myeloma underwent clinically indicated whole-body PCD-CT. The image quality of PCD-CT was assessed qualitatively by three independent radiologists for overall image quality, edge sharpness, image noise, lesion conspicuity, and diagnostic confidence using a 5-point Likert scale (5 = excellent), and quantitatively for signal homogeneity using the coefficient of variation (CV) of Hounsfield Units (HU) values and modulation transfer function (MTF) via the full width at half maximum (FWHM) in the frequency space. The results were compared with those of the current clinical standard EID-CT protocols as controls. Additionally, the radiation dose (CTDIvol) was determined. Results: We enrolled 35 patients with multiple myeloma (mean age 69.8 ± 9.1 years; 18 [51%] males). Qualitative image analysis revealed superior scores (median [interquartile range]) for PCD-CT regarding overall image quality (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), edge sharpness (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), image noise (4.0 [4.0-4.0] vs. 3.0 [3.0-4.0]), lesion conspicuity (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), and diagnostic confidence (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]) compared with EID-CT (P ≤ 0.004). In quantitative image analyses, PCD-CT compared with EID-CT revealed a substantially lower FWHM (2.89 vs. 25.68 cy/pixel) and a significantly more homogeneous signal (mean CV ± standard deviation [SD], 0.99 ± 0.65 vs. 1.66 ± 0.5; P < 0.001) at a significantly lower radiation dose (mean CTDIvol ± SD, 3.33 ± 0.82 vs. 7.19 ± 3.57 mGy; P < 0.001). Conclusion: Whole-body PCD-CT provides significantly higher subjective and objective image quality at significantly reduced radiation doses than the current clinical standard EID-CT protocols, along with readily available multi-spectral data, facilitating the potential for further advanced post-processing.
The Journal of Korean Institute of Electromagnetic Engineering and Science
/
v.20
no.9
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pp.868-882
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2009
In this paper, channel model and wireless link performance analysis for the short-range wireless communication system applications in the terahertz frequency which is currently interested in many countries will be described. In order to realize high data rates above 10 Gbps, the more wide bandwidths will be required than the currently available bandwidths of millimeter-wave frequencies, therefore, the carrier frequencies will be pushed to THz range to obtain larger bandwidths. From the THz atmospheric propagation characteristics based on ITU-R P.676-7, the available bandwidths were calculated to be 68, 48 and 45 GHz at the center frequencies of 220, 300 and 350 GHz, respectively. With these larger bandwidths, it was shown from the simulation that higher data rate above 10 Gbps can be achieved using lower order modulation schemes which have spectral efficiency of below 1. The indoor propagation delay spread characteristics were analyzed using a simplified PDP model with respect to building materials. The RMS delay spread was calculated to be 9.23 ns in a room size of $6\;m(L){\times}5\;m(W){\times}2.5\;m(H)$ for the concrete plaster with TE polarization, which is a similar result of below 10 ns from the Ray-Tracing simulation in the reference paper. The indoor wireless link performance analysis results showed that receiver sensitivity was $-56{\sim}-46\;dBm$ over bandwidth of $5{\sim}50\;GHz$ and antenna gain was calculated to be $26.6{\sim}31.6\;dBi$ at link distance of 10m under the BPSK modulation scheme. The maximum achievable data rates were estimated to be 30, 16 and 12 Gbps at the carrier frequencies of 220, 300 and 350 GHz, respectively, under the A WGN and LOS conditions, where it was assumed that the output power of the transmitter is -15 dBm and link distance of 1 m with BER of $10^{-12}$. If the output power of transmitter is increased, the more higher data rate can be achieved than the above results.
Kim, So-Ra;Kim, Eun-Sook;Nam, Youngwoo;Choi, Won Il;Kim, Cheol-Min
Korean Journal of Remote Sensing
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v.31
no.5
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pp.385-394
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2015
Pine wilt disease has greatly damaged pine forests not only in East Asia including South Korea and China, but also in European region. The damage caused by pine wood nematode (Bursaphelenchus xylophilus) is expressed in bundles within stands and rapidly spreading, however, present field survey methods have limitations to detecting damaged trees at regional level. This study extracted the damaged trees by pine wilt disease using time series hyperspectral aerial photographs, and analyzed their distribution characteristics. Hyperspectral aerial photographs of 1 meter spatial resolution were obtained in June, September, and October. Damaged trees by pine wilt disease were extracted using Normalized Difference Vegetation Index (NDVI) and Vegetation Index green (VIgreen) of the September photograph. Among extracted damaged trees, dead trees with leaves and without leaves were classified, and the spectral reflectance values from the photographs obtained in June, September, and October were compared to extract new outbreaks in September and October. Based on the time series dispersion of extracted damaged trees, nearest neighbor analysis was conducted to analyze distribution characteristics of the damaged trees within the region where hyperspectral aerial photographs were acquired. As a result, 2,262 damaged trees were extracted in the study area, and 604 dead trees (dead trees in last year) with leaves in relation to the damaged time and 300 and 101 newly damaged trees in September and October were classified. The result of nearest neighbor analysis using the data shows that aggregated distribution was the dominant pattern both previous and current year in the study area. Also, 80% of the damaged trees in current year were found within 60 m of dead trees in previous year.
It is important to identify geometries of fracture that act as a conduit of fluid flow for characterization of ground water flow in fractured rock. Fracture geometries control hydraulic conductivity and stream lines in a rock mass. However, we have difficulties to acquire whole geometric data of fractures in a field scale because of discontinuous distribution of outcrops and impossibility of continuous collecting of subsurface data. Therefore, it is needed to develop a method to describe whole feature of a target fracture geometry. This study suggests a new approach to develop a method to characterize on the whole feature of a target fracture geometry based on the Fourier transform. After sampling of specimens along a target fracture from borehole cores, effective frequencies among roughness components were selected by the Fourier transform on each specimen. Then, the selected effective frequencies were averaged on each frequency. Because the averaged spectrum includes all the frequency profiles of each specimen, it shows the representative components of the fracture roughness of the target fracture. The inverse Fourier transform is conducted to reconstruct an averaged whole roughness feature after low pass filtering. The reconstructed roughness feature also shows the representative roughness of the target subsurface fracture including the geometrical characteristics of each specimen. It also means that overall roughness feature by scaling up of a fracture. In order to identify the characteristics of permeability coefficients along the target fracture, fracture models were constructed based on the reconstructed roughness feature. The computation of permeability coefficient was performed by the homogenization analysis that can calculate accurate permeability coefficients with full consideration of fracture geometry. The results show a range between $10^{-4}{\;}and{\;}10^{-3}{\;}cm/sec$, indicating reasonable values of permeability coefficient along a large fracture. This approach will be effectively applied to the analysis of permeability characteristics along a large fracture as well as identification of the whole feature of a fracture in a field scale.
NA Jung-Yul;HAN Snag-Kyu;SEO Jang-Won;NOH Yi-Gn;KANG In-Sik
Korean Journal of Fisheries and Aquatic Sciences
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v.30
no.2
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pp.188-202
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1997
The seasonal variability of the sea surface winds over the last Sea of Korea (Japan Sea) is investigated by means of empirical orthogonal function (EOF) analysis. The combined representation of fields of three climatic variables by empirical orthogonal functions is discussed. The eigenvectors are derived from daily sea level pressure, wind speed and 10-day mean sea surface temperature (SST) during 15 years $(1978\~1992)$. The spatial patterns of the mean pressure are characterized by the high pressure in the western part and the low pressure in the eastern part. The spatial distribution of the standard deviation (SD) of pressure are characterized by max SD of 6.6 mb near the Vladivostok, and minima along the coast of the Japan. In Vladivostok, the maxima of SD of SST and south-north wind (WV) were also occurred. The representation of fields of individual meteorological variables by EOF shows that the first mode of the west-east wind (WU) explain over $47.3\%$ of the variance and the second mode of WU represents $30\%$. Especially, the first mode of the WV explain $70.9\%$ of the variance and their time series coefficients show 1-cpy, 0.5-cpy frequency spectrum. The spatial distribution of the first mode eigenvectors of SST are characterized by maximum near Vladivostok. The combined representation of fields of several variables (pressure, wind, SST) reveals that the first mode magnitudes of the variance of the combined eigenvectors (WU-PR) are increased. By means of this result, the 1-year peak and the 6-months peak are remarkable. In the three combined patterns (wind, pressure, SST), the second mode of the eigenvector (wind) is affected by the SST. Their time coefficients of the first mode show noticeable 1-year peak. The spectral analysis of the second mode shows broad seasonal signal with the period of 4-months and a significant peak of variability at 3-month period.
The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.
Objectives: 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. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or 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 was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The 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. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.10
no.1
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pp.100-112
/
2005
Soil temperature was measured from the surface to 40 cm depth at three stations with different heights in tidal flat of Gomso Bay, west coast of Korea, for one month in every season 2004 to examine the thermal structure and the variation. Mean temperature in surface layer was higher in summer and lower in winter than in lower layer, reflecting the seasonal variation of vertically propagating structure of temperature by heating and cooling from the tidal flat surface. Standard deviation of temperature decreased from the surface to lower layer. Periodic variations of solar radiation energy and tide mainly caused short term variation of soil temperature, which was also intermittently influenced by precipitation and wind. Time series analysis showed the power spectral energy peaks at the periods of 24, 12 and 8 hours, and the strongest peak appeared at 24 hour period. These peaks can be interpreted as temperature waves forced by variations of solar radiation, diurnal tide and interaction of both variations, respectively. EOF analysis showed that the first and the second modes resolved 96% of variation of vertical temperature structure. The first mode was interpreted as the heating antl cooling from tidal flat surface and the second mode as the effect of phase lag produced by temperature wave propagation in the soil. The phase of heat transfer by 24 hour period wave, analyzed by cross spectrum, showed that mean phase difference of the temperature wave increased almost linearly with the soil depth. The time lags by the phase difference from surface to 10, 20 and 40cm were 3.2,6.5 and 9.8 hours, respectively. Vertical thermal diffusivity of temperature wave of 24 hour period was estimated using one dimensional thermal diffusion model. Average diffusivity over the soil depths and seasons resulted in $0.70{\times}10^{-6}m^2/s$ at the middle station and $0.57{\times}10^{-6}m^2/s$ at the lowest station. The depth-averaged diffusivity was large in spring and small in summer and the seasonal mean diffusivity vertically increased from 2 cm to 10 cm and decreased from 10 cm to 40 cm. Thermal propagation speeds were estimated by $8.75{\times}10^{-4}cm/s,\;3.8{\times}10{-4}cm/s,\;and\;1.7{\times}10^{-4}cm/s$ from 2 cm to 10 cm, 20 cm and 40 cm, respectively, indicating the speed reduction with depth increasing from the surface.
A 21-residue peptide corresponding to amino acids 84-104 of $p16^{INK4A}$, the tumor suppressor, has been synthesized and its structure was studied by Circular Dichroism, $^1H$ NMR spectroscopy and molecular modeling. A p16-derived peptide (84-104 amino acids) forming stable complex with CDK4 and CDK6 inhibits the ability of CDK4/6 to phosphorylate pRb in vitro, and blocks cell-cycle progression through G1/S phase as shown in the function of the full-length p16. Its NMR spectral data including NOEs, $^3J_{NH-H{\alpha}}$ coupling constants, $C_{\alpha}H$ chemical shift, the average amplitude of amide chemical shift oscillation and temperature coefficients indicate that the secondary structure of a p16-derived peptide is similar to that of the same region of full-length p16, which consists of helix-turn-helix structure. The 3-D distance geometry structure based on NOE-hased distance and torsion angle restraints is characterized by ${\gamma}$-turn conformation between residues $Gly^{89}-Leu^{91}$(${\varphi}_{i+1}=-79.8^{\circ}$, ${\varphi}_{i+1}=60.2^{\circ}$) as evidenced in a single crystal structure for the corresponding region of p18 or p19, but is undefined at both the N and C termini. This compact and rigid ${\gamma}$-turn region is considered to stabilize the structure of p16-derived peptide and serve as a site recognizing cyelin dependent kinase, and this well-defined ${\gamma}$-turn structure could be utilized for the design of anti-cancer drug candidates.
Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.
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