Kwon, Oh Jun;Hur, Jae;Lee, Han Wool;Kim, Joo Yeon;Park, Min Soo;Roo, Dong Ook;Kang, Chun Goo;Kim, Jae Sam
The Korean Journal of Nuclear Medicine Technology
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v.19
no.1
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pp.30-36
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2015
Purpose Whole body bone scan, which makes up a largest percentage of nuclear medicine tests, has high sensitivity and resolution about bone lesion like osteomyelitis, fracture and the early detection of primary cancer. However, any standard for valuation has not yet been created except minimum factor. Therefore, in this study, we will analysis the method which show a quantitative evaluation index in whole body bone scan. Materials and Methods This study is conducted among 30 call patients, who visited the hospital from April to September 2014 with no special point of view about bone lesion, using GE INFINIA equipment. Enumerated data is measured mainly with patient's whole body count and lumbar vertabrae, and the things which include CNR (Contrast to Noise ratio), SNR (Signal to Noise ratio) are calculated according to the mean value signal and standard deviation of each lumbar vertabrae. In addition, the numerical value with the abdominal thickness is compared to each value by the change of scan speed and tissue equivalent material throughout the phantom examination, and compared with 1hours deleyed value. Completely, on the scale of ten, 2 reading doctors and 5 skilled radiologists with 5-years experience analysis the correlation between visual analysis with blind test and quantitative calculation. Results The whole body count and interest region count of patients have no significant correlation with visual analysis value throughout the blind test(P<0.05). There is definite correlation among CNR and SNR. In phantom examination, Value of the change was caused by the thickness of the abdomen and the scan speed. And The poor value of the image in the subject as a delay test patient could be confirmed that the increase tendency. Conclusion Now, a standard for valuation has not been created in whole body bone scan except minimum factor. In this study, we can verify the significant correlation with blind test using CNR and SNR and also assure that the scan speed is a important factor to influence the imagine quality from the value. It is possible to be some limit depending on the physiology function and fluid intake of patient even if we progress the evaluation in same condition include same injection amount, same scan speed and so on. However, that we prove the significant evaluation index by presenting quantitative calculation objectively could be considered academic value.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.33
no.4
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pp.317-324
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2015
GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (Tm), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.
Kim, Jee-Won;Ahn, Hyeong-Sook;Kim, Kyung-Ah;Lim, Young;Yun, Im-Goung
Tuberculosis and Respiratory Diseases
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v.42
no.6
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pp.923-933
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1995
Background: Pleural abnormality is the the most common respiratory change caused by asbestos dust inhalation and also develop other asbestos related disease after cessation of asbestos exposure. So we conducted epidemiologic study to investigate if the pleural abnormality is associated with pulmonary function change and what factors are influenced on pulmonary function impairment. Methods: Two hundred and twenty two asbestos workers from 9 industries using asbestos in Korea were selected to measure the concentration of sectional asbestos fiber. Ouestionnaire, chest X-ray, PFT were also performed. All the data were analyzed by student t-test and chi-square test using SAS. Regressional analysis was performed to evaluate important factors, for example smoking, exposure concentration, period and the existence of pleural thickening, affecting to the change of pulmonary function. Results: 1) All nine industries except two, airborn asbestos fiber concentration was less than an average permissible concentration. PFT was performed on 222 workers and the percentage of male was 88.3%, their mean age was $41{\pm}9$ years old, and the duration of asbestos exposure was $10.6{\pm}7.8$ yrs. 2) The chest X-ray showed normal(89.19%), pulmonary Tb(inactive)(2.7%), pleral thickening (7.66%), suspected reticulonodular shadow(0.9%). 3) The mean values of height, smoking status, concentration of asbestos fiberwere not different between the subjects with pleural thickening and others, but age, cumulative pack-years, the duration of asbestos exposure were higher in subjects with pleural thickening. 4) All the PFT indices were lower in the subjects with pleural thickening than in the subjects without pleural thickening. 5) Simple regression analysis showed there was a significant correlation between $FEF_{75}$ which is sensitive in small airway obstruction and cumulative smoking pack-years, the duration of asbestos exposure and the concentration of asbestos fiber. 6) Multiple regression analysis showed all the pulmonary function indices were decreased as the increase of cumulative smoking pack-years and especially in the indices those are sensitive in small airway obstruction. Pleural thickening was associated with reduction in FVC, $FEV_1$, PEFR and $FEF_{25}$. Conclusion: The more concentration of asbestos fiber and the more duration of asbestos exposure, the greater reduction in $FEF_{50}$, $FEF_{75}$. Therefore PFT was important in the evaluation of early detection for small airway obstruction. Furthermore pleural thickening without asbesto-related parenchymal lung disease is associated with reduction in pulmonary function.
Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.
Purpose : Early degeneration of articular cartilage is accompanied by a loss of glycosaminoglycan (GAG) and the consequent change of the integrity. The purpose of this study was to biochemically quantify the loss of GAG, and to evaluate the $Gd(DTPA)^{2-}$-enhanced, and T1, T2, rho relaxation map for detection of the early degeneration of cartilage. Materials and Methods : A cartilage-bone block in size of $8mm\;\times\;10mm$ was acquired from the patella in each of three pigs. Quantitative analysis of GAG of cartilage was performed at spectrophotometry by use of dimethylmethylene blue. Each of cartilage blocks was cultured in one of three different media: two different culture media (0.2 mg/ml trypsin solution, 1mM Gd $(DTPA)^{2-}$ mixed trypsin solution) and the control media (phosphate buffered saline (PBS)). The cartilage blocks were cultured for 5 hrs, during which MR images of the blocks were obtained at one hour interval (0 hr, 1 hr, 2 hr, 3 hr, 4 hr, 5 hr). And then, additional culture was done for 24 hrs and 48 hrs. Both T1-weighted image (TR/TE, 450/22 ms), and mixed-echo sequence (TR/TE, 760/21-168ms; 8 echoes) were obtained at all times using field of view 50 mm, slice thickness 2 mm, and matrix $256\times512$. The MRI data were analyzed with pixel-by-pixel comparisons. The cultured cartilage-bone blocks were microscopically observed using hematoxylin & eosin, toluidine blue, alcian blue, and trichrome stains. Results : At quantitation analysis, GAG concentration in the culture solutions was proportional to the culture durations. The T1-signal of the cartilage-bone block cultured in the $Gd(DTPA)^{2-}$ mixed solution was significantly higher ($42\%$ in average, p<0.05) than that of the cartilage-bone block cultured in the trypsin solution alone. The T1, T2, rho relaxation times of cultured tissue were not significantly correlated with culture duration (p>0.05). However the focal increase in T1 relaxation time at superficial and transitional layers of cartilage was seen in $Gd(DTPA)^{2-}$ mixed culture. Toluidine blue and alcian blue stains revealed multiple defects in whole thickness of the cartilage cultured in trypsin media. Conclusion : The quantitative analysis showed gradual loss of GAG proportional to the culture duration. Microimagings of cartilage with $Gd(DTPA)^{2-}$-enhancement, relaxation maps were available by pixel size of $97.9\times195\;{\mu}m$. Loss of GAG over time better demonstrated with $Gd(DTPA)^{2-}$-enhanced images than with T1, T2, rho relaxation maps. Therefore $Gd(DTPA)^{2-}$-enhanced T1-weighted image is superior for detection of early degeneration of cartilage.
Park, Jong-Sung;Park, So-Young;Oh, Je-Ill;Jeong, Sang-Jo;Lee, Min-Ju;Her, Nam-Guk
Journal of Korean Society of Environmental Engineers
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v.31
no.2
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pp.79-89
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2009
Naphthalene is a volatile, hydrophobic, and possibly carcinogenic compound that is known to have a severe detrimental effect to aquatic ecosystem. Our research examined the effects of various operating conditions (temperature, pH, initial concentration, and frequency and type of ultrasound) on the sonochemical degradation of naphthalene and OH radical production. The MDL (Method detection limit) determined by LC/FLD (1200 series, Agilient) using C-18 reversed column is measured up to 0.01 ppm. Naphthalene vapor produced from ultrasound irradiation was detected under 0.05 ppm. Comparison of naphthalene sonodegradion efficiency tested under open and closed reactor cover fell within less than 1% of difference. Increasing the reaction temperature from $15^{\circ}C$ to $40^{\circ}C$ resulted in reduction of naphthalene degradation efficiency ($15^{\circ}C$: 95% ${\rightarrow}$$40^{\circ}C$: 85%), and altering pH from 12 to 3 increased the effect (pH 12: 84% ${\rightarrow}$pH 3: 95.6%). Pseudo first-order constants ($k_1$) of sonodegradation of naphthalene decreased as initial concentration of naphthalene increased (2.5 ppm: $27.3{\times}10^{-3}\;min^{-3}\;{\rightarrow}$ 10 ppm : $19.3{\times}10^{-3}\;min^{-3}$). Degradation efficiency of 2.5 ppm of naphthalene subjected to 28 kHz of ultrasonic irradiation was found to be 1.46 times as much as when exposed under 132 kHz (132 kHz: 56%, 28 kHz: 82.7%). Additionally, its $k_1$ constant was increased by 2.3 times (132 kHz: $2.4{\times}10^{-3}\;min^{-1}$, 28 kHz: $5.0{\times}10^{-3}\;min^{-1}$). $H_2O_2$ concentration measured 10 minutes after the exposure to 132 kHz of ultrasound, when compared with the measurement under frequency of 28 kHz, was 7.2 times as much. The concentration measured after 90 minutes, however, showed the difference of only 10%. (concentration of $H_2O_2$ under 28 kHz being 1.1 times greater than that under 132 kHz.) The $H_2O_2$ concentration resulting from 2.5 ppm naphthalene after 90 minutes of sonication at 24 kHz and 132 kHz were lower by 0.05 and 0.1 ppm, respectively, than the concentration measured from the irradiated M.Q. water (no naphthalene added.) Degradation efficiency of horn type (24 kHz) and bath type (28 kHz) ultrasound was found to be 87% and 82.7%, respectively, and $k_1$ was calculated into $22.8{\times}10^{-3}\;min^{-1}$ and $18.7{\times}10^{-3}\;min^{-1}$ respectively. Using the multi- frequency and mixed type of ultrasound system (28 kHz bath type + 24 kHz horn type) simultaneously resulted in combined efficiency of 88.1%, while $H_2O_2$ concentration increased 3.5 times (28 kHz + 24 kHz: 2.37 ppm, 24 kHz: 0.7 ppm.) Therefore, the multi-frequency and mixed type of ultrasound system procedure might be most effectively used for removing the substances that are easily oxidized by the OH radical.
Soybean is one of the most common food materials causing food hypersensitivity reactions in Korea. In this study, we have investigated the effect of roasting and fermentation on the allergenicity of soybean. Three kinds of soybean ($Daepung$, $Daewon$, and $Taegwang$) were prepared as raw, roasted, and fermented by $Bacillus$$subtilis$ GSK 3580, and then their proteins were extracted. The proteins were separated using SDS-PAGE, and the detection of IgE specific to soybean proteins was performed by immunoblotting using 7 sera of soybean allergy patients and non-allergic control individuals. Serum specific IgE to soybean was measured by ELISA. The SDS-PAGE of raw soybean proteins showed various-sized bands ranging from 9 to 76 kDa, which are known as major allergens. In particular, 9, 21, 34, 52, 72, and 76 kDa proteins are known as LTP, Kunits trypsin inhibitor, $Gly$ m Bd 30K, ${\beta}$-subunit, ${\alpha}$-subunit, and ${\alpha}$'-subunit of ${\beta}$-conglycinin, respectively; these are major allergens in soybean. In contrast, only peptides of less than 35 kDa were found in roasted and fermented soybeans. IgE immunoblot analysis of three roasted species of soybeans commonly detected at 38-40 kDa and 10-15 kDa. The protein bands in fermented soybean showed very weak signals or were not detected. In addition, the reactivity of most patients' sera to soybean was decreased after roasting and fermentation. With these results, it may be concluded that the allergenicity of soybeans is reduced by the roasting and fermentation processes. It is supposed that allergenic proteins in soybean were degraded by heat treatment methods and proteolytic enzymes were secreted from fermenting microorganisms.
By the standards and specifications for hygiene products, three test methods for formaldehyde are specified for each item type of hygiene product. After derivatization using acetylacetone and 2,4-dinitrophenylhydrazine (2,4-DNPH), formaldehyde is analyzed by spectrophotometer and high-performance liquid chromatography (HPLC). Validation of the three test methods was performed on tissue, diaper lining and waterproof layer, and panty liner products. The results of linearity (R2), limit of detection (LOD), limit of quantification (LOQ), recovery rate (%) and reproducibility (%), showed that all three methods are suitable for analyzing formaldehyde in hygiene products. After derivatization with 2,4-DNPH and cetylacetone, formaldehyde was analyzed at 0, 3, 6, 9, 24 and 48 hours by HPLC. Formaldehyde derivatized with 2,4-DNPH showed no statistically significant change in formaldehyde peak area over time (P>0.05). But, acetylacetone-derivatizated formaldehyde showed a negative correlation coefficient (r) over time (P<0.01). We investigated the residual amounts of formaldehyde in 205 hygiene products distributed in Busan. Among 74 disposable diaper products tested, 73 had low concentrations of formaldehyde (0.13-29.87 mg/kg). Moreover, formaldehyde was not detected in any of 78 tissue, 27 disposable paper towel, 12 disposable dishcloth, 7 paper cup, one brand of paper straw and 6 disposable napkin products.
At a recent medical imaging technology, the major issue of X-ray diagnosis in breast cancer is the early detection of breast cancer and low patient's exposure dose. As one of studies to acquire a monochromatic X-ray, Technologies using multilayer mirror had been preceded. However, a uniform multilayer mirror that consists of uniform thin-film thickness can acquire a monochromatic X-ray only in the partial area corresponds to angle of incidence of white X-ray, so there are limits for X-ray imaging technology applications. In this study, we designed laterally graded multilayer mirror(below GML) that reflects same monochromatic X-ray over the entire area of thin-film mirror, which have the the thickness of the linear gradient that correspond to angle of incidence of white X-ray. By using ion-beam sputtering system added the mask control system we fabricated a GML which has size of $100{\times}100mm^2$. The GML is designed to achieve the monochromatic X-ray of 17.5kev energy and has thin-film thickness change from 4.62nm to 6.57nm(3.87nm at center). It reflects the monochromatic X-ray with reflectivity of more than 60 percent, FWHM of below 2.6keV and X-ray beam width of about 3mm. The monochromatic X-ray corresponded to 17.5keV using GML would have wide application in development of mammography system with high contrast and low dose.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1031-1031
/
2001
The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.
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