• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.880-890
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• 2010

The intrasvascular ultrasound (IVUS) imaging technique is used to diagnose cerebrovascular diseases such as stroke. Recently, elasticity imaging methods have been investigated to diagnose blood clots attached to blood vessel intima. However, the IVUS imaging technique is an invasive method that requires a transducer to be inserted into blood vessel. In this paper, strain images are obtained of blood clots attached to blood vessel intima with data acquired from outside the blood vessel using a linear array transducer. In order to measure the displacement of blood vessel accurately, experimental data are acquired by steering ultrasound beams so that they can intersect the blood vessel wall at right angles. The acquired rf data are demodulated to the baseband. The resulting complex baseband signals are then processed by an autocorrelation algorithm to compute the blood vessel movement and thereby produce strain image. This proposed method is verified by experiments on a plastic blood vessel mimicking phantom. The efficacy of the proposed method was verified using a home-made blood vessel mimicking phantom. The blood vessel mimicking phantom was constructed by making a 6 mm diameter hollow cylinder inside it to simulate a blood vessel and adhering 2 mm thick soft plaque to the inner wall of the hollow cylinder. The RF data were acquired using a clinical ultrasound scanner (Accuvix XQ, Medison, Seoul. Korea) with a 7.5 MHz linear array transducer by steering ultrasound beams in steps of $1^{\circ}$ from $-40^{\circ}$ to $40^{\circ}$ for a total of 81 angles. Experimental results show that the plaque region near the blood vessel wall is softer than background tissue. Although the imaging region is restricted due to the limited range of angles for which scan lines are perpendicular to the wall, the feasibility of strain imaging is demonstrated.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.633-640
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• 2006

Spatial clustering, which groups similar objects based on their distance, connectivity, or their relative density in space, is an important component of spatial data mining. Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Clustering large data sets has always been a serious challenge for clustering algorithms, because huge data set would make the clustering process extremely costly. In this paper, we propose an enhanced Density-Grid based Clustering algorithm for Large spatial database by setting a default number of intervals and removing the outliers effectively with the help of a proper measurement to identify areas of high density in the input data space. We use a density threshold DT to recognize dense cells before neighbor dense cells are combined to form clusters. When proposed algorithm is performed on large dataset, a proper granularity of each dimension in data space and a density threshold for recognizing dense areas can improve the performance of this algorithm. We combine grid-based and density-based methods together to not only increase the efficiency but also find clusters with arbitrary shape. Synthetic datasets are used for experimental evaluation which shows that proposed method has high performance and accuracy in the experiments.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.49-60
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• 2022

Underground urbanization appears to be a promising solution in response to the shortage of construction sites in the above-ground space. In this context, an accurate evaluation of a construction site ensures the long-term performance of geosystems. This study characterizes potential sites for complex plants built in underground space using geophysical methods (i.e., seismic refraction exploration and electrical resistivity survey) and in situ tests (i.e., standard penetration tests (SPTs) and downhole tests). SPTs are conducted in nine boreholes BH-1-BH-9 to estimate the groundwater level and vertical distribution of geological structures. The seismic refraction method enables us to obtain the elastic wave velocity and thickness of each soil layer for each cross-sectional area. An electrical resistivity survey conducted using the dipole array method provides the electrical resistivity profiles of the cross-sectional area. Data obtained using geophysical techniques are used to assess the classification of the soil layer and bedrock, particularly the fracture zone. This study suggests that geotechnical information using in situ tests and geophysical methods are useful references to design an underground complex plant construction.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.164-178
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• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.52-60
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• 1999

Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

• Progress in Medical Physics
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• v.26 no.3
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• pp.168-177
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• 2015

For evaluating the treatment planning accurately, the quality assurance for treatment planning is recommended when patients were treated with IMRT which is complex and delicate. To realize this purpose, treatment plan quality assurance software can be used to verify the delivered dose accurately before and after of treatment. The purpose of this study is to evaluate the accuracy of treatment plan quality assurance software for each IMRT plan according to MLC DLG (dosimetric leaf gap). Novalis Tx with a built-in HD120 MLC was used in this study to acquire the MLC dynalog file be imported in MobiusFx. To establish IMRT plan, Eclipse RTP system was used and target and organ structures (multi-target, mock prostate, mock head/neck, C-shape case) were contoured in I'mRT phantom. To verify the difference of dose distribution according to DLG, MLC dynalog files were imported to MobiusFx software and changed the DLG (0.5, 0.7, 1.0, 1.3, 1.6 mm) values in MobiusFx. For evaluation dose, dose distribution was evaluated by using 3D gamma index for the gamma criteria 3% and distance to agreement 3 mm, and the point dose was acquired by using the CC13 ionization chamber in isocenter of I'mRT phantom. In the result for point dose, the mock head/neck and multi-target had difference about 4% and 3% in DLG 0.5 and 0.7 mm respectively, and the other DLGs had difference less than 3%. The gamma index passing-rate of mock head/neck were below 81% for PTV and cord, and multi-target were below 30% for center and superior target in DLGs 0.5, 0.7 mm, however, inferior target of multi-target case and parotid of mock head/neck case had 100.0% passing rate in all DLGs. The point dose of mock prostate showed difference below 3.0% in all DLGs, however, the passing rate of PTV were below 95% in 0.5, 0.7 mm DLGs, and the other DLGs were above 98%. The rectum and bladder had 100.0% passing rate in all DLGs. As the difference of point dose in C-shape were 3~9% except for 1.3 mm DLG, the passing rate of PTV in 1.0 1.3 mm were 96.7, 93.0% respectively. However, passing rate of the other DLGs were below 86% and core was 100.0% passing rate in all DLGs. In this study, we verified that the accuracy of treatment planning QA system can be affected by DLG values. For precise quality assurance for treatment technique using the MLC motion like IMRT and VMAT, we should use appropriate DLG value in linear accelerator and RTP system.

• Parasites, Hosts and Diseases
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• v.30 no.2
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• pp.65-74
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• 1992

The tegumental ultrastructure of juvenile and adult Echinostoma cinetorchis (Trematoda: Echinostomatidae) was observed by scanning electron microscopy. Three-day (juvenile) and 16-day (adult) worms were harvested from rats (Sprague-Dawley) experimentally fed the metacercariae from the laboratory-infected fresh water snail, Hippeutis cantori. The worms were fifed with 2.5% glutaraldehyde, processed routinely, and observed by an ISI Korea DS-130 scanning electron microscope. The 3-day old juvenile worms were elongated and ventrally curved, with their ventral sucker near the anterior two-fifths of the body. The head crown was bearing 37∼38 collar spines arranged in a zigzag pattern. The lips of the oral and ventral suckers had 8 and 5 type II sensory papillae respectively, and bewteen the spines, a few type III papillae were observed. Tongue or spade-shape spines were distributed anteriorly to the ventral sucker, whereas peg-like spines were distributed posteriorly and became sparse toward the posterior body. The spines of the dorsal surface were similar to those of the ventral surface. The 16-day old adults were leaf-like, and their oral and ventral suckers were located very closely. Aspinous head crown, oral and ventral suckers had type II and type III sensory papillae, and numerous type I papillae were distributed on the tegument anterior to the ventral sucker. Scale-like spines, with broad base and round tip, were distributed densely on the tegument anterior to the ventral sucker but they became sparse posteriorly. At the dorsal surface, spines were observed at times only at the anterior body. The results showed that the tegument of E. cinetorchis is similar to that of other echinostomes, but differs in the number and arrangement of collar spines, shape and distribution of tegumenal spines, and type and distribution of sensory papillae.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.89-97
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• 2004

The objective of this study is the development of a scheme and discrete optimum design algorithm, which is based on the genetic algorithm. The algorithm can perform both scheme and size optimum designs of plane trusses. The developed Scheme genetic algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. However, its application to the complicated structures has been limited because of the extreme time need for a number of structural analyses. This study solves the problem by introducing the size & scheme genetic algorithm operators into the genetic algorithm. The genetic process virtually takes no time. However, the evolutionary process requires a tremendous amount of time for a number of structural analyses. Therefore, the application of the genetic algorithm to the complicated structures is extremely difficult, if not impossible. The scheme genetic algorithm operators was introduced to overcome the problem and to complement the evolutionary process. It is very efficient in the approximate analyses and scheme and size optimization of plane trusses structures and considerably reduces structural analysis time. Scheme and size discrete optimum combined into the genetic algorithm is what makes the practical discrete optimum design of plane fusses structures possible. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to various optimum design examples: plane pratt, howe and warren truss.