• Journal of Internet Computing and Services
• /
• v.17 no.1
• /
• pp.101-107
• /
• 2016

Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

• Journal of Soil and Groundwater Environment
• /
• v.11 no.1
• /
• pp.14-22
• /
• 2006

Laboratory column experiment for simultaneous removal of Cd and Cr(VI) were conducted using newly developed material of Fe-loaded zeolite having both reduction ability and sorption capacity. The solution containing Cd and Cr(VI) was injected into the column and the breakthrough curves (BTCs) for the contaminants were observed at the effluent port. Cd breakthrough was not initialized until Cr(VI) breakthrough was completed. Therefore it could be concluded that overall efficiency of Fe-loaded zeolite should be determined by the reactivity for Cr(VI). The relative concentration of Cr(VI) BTC increased to the unit value while initial breakthrough was delayed and the propagation of breakthrough was slowed. In order to quantitatively describe the shape of Cr(VI) BTC, new parameters of ${\alpha}\;and\;{\beta}$ designated to be shape parameters, were defined and applied in contaminant transport concentration. These parameters were employed to represent the degree of initial breakthrough delay and the degree of breakthrough propagation, respectively. As initial contaminant concentration increased, ${\alpha}$ decreased, which indicated the delay of BTC's initiation. And as initial contaminant flow rate increased, ${\beta}$ decreased, which represented the faster propagation of the BTC. From these results, Fe-loaded zeolite was found to be an effective reactive material for PRBs against heavy metals having different ionic forms in groundwater. And it could be expected that as groundwater flows faster, the propagation of breakthrough would be faster and as contaminant concentration is higher, the initial point of breakthrough would appear earlier.

• Korean Journal of Cognitive Science
• /
• v.27 no.2
• /
• pp.159-219
• /
• 2016

Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.

• Journal of Bio-Environment Control
• /
• v.22 no.3
• /
• pp.284-290
• /
• 2013

This study analyzed the geometric, compressive, cutting and friction properties of oriental melons in order to design a gripper capable of soft handling and a cutter for cutting oriental melon vine among the end effector of oriental melon as a preliminary step for developing the end effector of the robot capable of harvesting oriental melons in protected cultivation. As a result, the average length, diameter at the midpoint, weight, volume and roundness of the oriental melons were 108 mm, 70 mm, 188 g, 333 mL and 3.8 mm. Nonlinear regression analysis was performed on the equation $W=L^a{\times}D_2^b$ with variation of the length (L) and diameter (D2) of the weight (W) of the oriental melons. As a result, it was shown that there was a correlation between a of 2.0279 and b of -0.9998 as a constant value. The average diameter of the oriental melon vine was 3.8 mm, and most vines were distributed within a radius of 5 mm from the center. The average yield value, compressive strength and hardness of the oriental melons were $36.5N/cm^2$, $185.7N/cm^2$ and $636.7N/cm^2$, respectively. The average cutting force and shear strength of the oriental melon vines were $2.87{\times}10^{-2}\;N$ and $5.60N/cm^2$, respectively. The maximum friction coefficient of the oriental melons was rubber of 0.609, followed by aluminium of 0.393, stainless steel of 0.177 and teflon of 0.079. It was considered possible to apply it to the size of the gripper and cutter, turning radius, dynamics of drive motor and selection of materials and their quality in light of the position error and safety factor according to the movement when designing end effector based on the analyzed data.

• Investigative Magnetic Resonance Imaging
• /
• v.10 no.2
• /
• pp.98-107
• /
• 2006

Magnetization Transfer (MT) imaging generates contrast dependent on the phenomenon of magnetization exchange between free water proton and restricted proton in macromolecules. In biological materials in knee, MT or cross-relaxation is commonly modeled using two spin pools identified by their different T2 relaxation times. Two models for cross-relaxation emphasize the role of proton chemical exchange between protons of water and exchangeable protons on macromolecules, as well as through dipole-dipole interaction between the water and macromolecule protons. The most essential tool in medical image manipulation is the ability to adjust the contrast and intensity. Thus, it is desirable to adjust the contrast and intensity of an image interactively in the real time. The proton density (PD) and T2-weighted SE MR images allow the depiction of knee structures and can demonstrate defects and gross morphologic changes. The PD- and T2-weighted images also show the cartilage internal pathology due to the more intermediate signal of the knee joint in these sequences. Suppression of fat extends the dynamic range of tissue contrast, removes chemical shift artifacts, and decreases motion-related ghost artifacts. Like fat saturation, phase sensitive methods are also based on the difference in precession frequencies of water and fat. In this study, phase sensitive methods look at the phase difference that is accumulated in time as a result of Larmor frequency differences rather than using this difference directly. Although how MT work was given with clinical evidence that leads to quantitative model for MT in tissues, the mathematical formalism used to describe the MT effect applies to explaining to evaluate knee disorder, such as anterior cruciate ligament (ACL) tear and meniscal tear. Calculation of the effect of the effect of the MT saturation is given in the magnetization transfer ratio (MTR) which is a quantitative measure of the relative decrease in signal intensity due to the MT pulse.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.40 no.3
• /
• pp.273-283
• /
• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Economic and Environmental Geology
• /
• v.45 no.6
• /
• pp.673-684
• /
• 2012

Quantitative understanding of total carbon, total inorganic carbon and total organic carbon contained in ocean sediments is a basic data for interpretation of oceanic sediment environments. Elemental analyzer(EA) is frequently used for the analysis of carbon contents in inland soils and ocean sediments. Carbon and nitrogen contents of the soil reference material analyzed by an EA were 2.30% and 0.21% with standard deviations of 0.02 and 0.01, respectively. Relative standard deviations were 0.01 and 0.06, respectively, representing a high precision. Regression analysis of TOC and TC analysis results for the samples with TOC of less than 2.0% for the site in Hyung-Do showed a linear relationship with a slope of 0.9743($R^2$=0.9989, n=38), and the results of a relationship regression analysis between total organic carbon contents less than 0.5% and average grain size except for two samples showed a linear relationship with a slope of 0.0444($R^2$=0.6937 n=36). TOC contents of surface sediments were in the ranges of 0.10~1.67%(Average $0.26{\pm}0.37%$) with TOC values of 1.67% at S02 sampling site, 1.13% at S07 sampling site, and less than 1.00% at remaining sites. In the case of PC 01 core sediments, TOC showed the highest value of 0.20% near 70 cm. In the case of PC 02 core sediments, the highest value of 0.24% was indicated near 60 cm. The analysis method of organic carbon obtained from Hyung-Do Intertidal zone sediment sample results may be considered applicable to an organic carbon analysis for ocean sediments and useful for organic carbon analysis experiments of ocean sediments with a reduction in time required for the analysis and a high precision coupled with a high accuracy.

• Environmental Analysis Health and Toxicology
• /
• v.15 no.4
• /
• pp.131-137
• /
• 2000

The release of hazardous waste materials into the environment poses serious risks in humans and ecosystems. The risk assessment of environmental pollutants including hazardous chemicals requires a comprehensive measurement of hazard and exposure of the chemicals that can be achieved by toxicity evaluation using a biological system such as biomarkers. In this report we have tried to develop a biomarker used to elucidate a molecular basis of, and to monitor abnormal behaviors caused by diazinon in Japanese medaka (Oryzias latipes) as a model organism. First, an attempt was made to clone tyrosine hydroxylase gene from Japanese medaka that would be a candidate for a biomarker for neuronal modulations and behaviors. For monitoring experiments at behavioral and molecular biological levels, the fish were treated under different sublethal conditions of diazinon and their behavioral responses were observed . In this study we have successfully cloned a partial TH gene from the medaka fish through PCR screening of an ovary cDNA library. DNA sequencing analysis revealed that the amplified fragment was 327 bp encoding 109 amino acids. Comparing the DNA sequence of medaka TH with other species, TH gene revealed the DNA sequence was completely identical to that of rat TH. In the RT-PCR, 330 Up of mRNA was consistently amplified in all the treated samples including control There were no significant differences in the TH expression level regardless of treating concentrations (1∼5,000 ppb) and time (0∼48 hr) The reason appeared to be that RT-PCR was not performed using through a quantitative analysis normalized against an actin gene expression. Organ or tissue - specific detection of TH activity and mRNA as biomarkers will be a useful monitoring tool for neurobehavioral changes in fish influenced by toxic chemicals. Furthermore, quantitative analysis of locomotive patterns and its correlation with the neurochemical and molecular data would be highly useful in measuring toxicity and hazard ofvarious environmental pollutants.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.4 no.1
• /
• pp.33-40
• /
• 2006

The characteristics of the aluminum waste melting and the distribution of the radioactive nuclides have been investigated for the estimation on the volume reduction and the decontamination of the aluminum wastes from the decommissioning of the TRIGA MARK it and III research reactors at the Korea Atomic Energy Research Institute(KAERI). The aluminum wastes were melted with the use of the fluxes such as flux $A:NaCl-KCl-Na_3AlF_6$, flux B:NaCl-NaF-KF, flux $C:CaF_2$, and flux $D:LiF-KCl-BaCl_2$ in the DC graphite arc furnace. For the assessment of the distribution of the radioactive nuclides during the melting of the aluminum, the aluminum materials were contaminated by the surrogate nuclides such as cobalt(Co), cesium(Cs) and strontium(Sr). The fluidity of aluminum melt was increased with the addition of the fluxes, which has slight difference according to the type of fluxes. The formation of the slag during the aluminum melting added the flux type C and D was larger than that with the flux A and B. The rate of the slag formation linearly increased with increasing the flux concentration. The results of the XRD analysis showed that the surrogate nuclide was transferred to the slag, which can be easily separated from the melt and then they combined with aluminum oxide to form a more stable compound. The distribution ratio of cobalt in ingot to that in slag was more than 40% at all types of fluxes. Since vapor pressures of cesium and strontium were higher than those that of the host metals at the melting temperature, their removal efficiency from the ingot phase to the slag and the dust phase was by up to 98%.

• Analytical Science and Technology
• /
• v.29 no.2
• /
• pp.57-64
• /
• 2016

Many phthalic acid esters (PAEs), including DMP, DEP, DBP, BBP, and DEHP, as well as DEHA are widely used as plasticizers in plastics. An analytical method was developed and used to analyze these compounds at 41 industrial facilities. The coefficient of determination (R²) for each constructed curve was higher than 0.98. The method detection limit (MDL) values were 0.4–0.7 μg/L for PAEs and 0.6 μg/L for DEHA. In addition, the recovery rate was shown to be 77.0–92.3%, while the relative standard deviation was shown to be in the range of 5.8-10.5%. DMP (n = 3), DEP (n = 2), DBP (n = 2), BBP (n = 2), and DEHA (n = 3) were detected in the range of 2.2-11.1% in the influent. DEHP was a predominant compound and was detected at > MDL in both the influent (n = 16, 35.6%) and the effluent (n = 4, 10.0%) at a high removal efficiency (92–100%). The highest levels of residue in industrial wastewater influent were 137.4 μg/L of DEHP at plastic products manufacturing facility, 12.5 μg/L of DEHA at a chemical manufacturing facility, and 14.0 μg/L of DEP at an electronics facility. The highest concentration of effluent was 12.5 μg/L of DEHP at a chemical manufacturing facility, which indicated that the effluent was below the allowable concentration (800 μg/L). Therefore, the levels of PAEs and DEHA that are discharged into nearby streams could not influence the health of the ecosystem.