• Applied Microscopy
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• v.50
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• pp.6.1-6.6
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• 2020

The cerebellum is a region of the brain that plays an important role in motor control. It is classified phylogenetically into archicerebellum, paleocerebellum and neocerebellum. The Purkinje cells are lined in a row called Purkinje cell layer and it has a unique dendritic branches with many spines. The previous study reported that there is a difference of synapse density according to the lobules based on large two-dimensional data. However, recent study with high voltage electron microscopy showed there was no differences in dendritic spine density of the Purkinje cell according to its phylogenetic lobule. We analyzed Purkinje cell density in the II, VI and X lobules by stereological modules and synaptic density was estimated by double disector based on Purkinje cell density in the molecular layer of each lobule. The results showed that there was significant difference in the Purkinje cell density and synapse number according to their phylogenetic lobules. The number of Purkinje cell in a given volume was larger in the archicerebellum, but synapse density was higher in the neocerebellum. These data suggest that cellular and synaptic organization of the Purkinje cell is different according to their phylogenetic background.

• Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.20-27
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• 2008

The characteristics of compressible flow are different from those of incompressible flow from the mathematical and physical point of view. Therefore, the way to solve the flowfield is different between compressible flow and incompressible flow. In general, density-based numerical algorithm is mainly used for compressible flow solver development. On the other hand, incompressible flow solver prefers to use pressure-based numerical algorithm. In this research, a compressible Navier-Stokes flow solver is developed by means of extending from pressure-based incompressible numerical algorithm to handle both compressible and incompressible flows using the same flow solver. The present flow solver is tested at various speed ranges and compared with the solutions of density-based compressible flow solver. Numerical results show a good agreement between two flow solvers.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1199-1204
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• 2005

The purpose of field monitoring system in KHC-Test Road located at Joongbu-Inland Highway, is to provide the performance data for traffic and environmental loadings from pavement surface. Among them, water content reflectometers(WCR) are used to measure the volumetric water content of subgrades soils used in test roads. However, most of the WCRs are not well-calibrated based on the field conditions. In this study, the laboratory based test is performed at various density conditions to evaluate the volumetric water content in subgrade Soils with a WCR. Based on the laboratory testings, the effect of density on WCR measurement are well evaluated for predicting the volumeric water content.of subgrades soils in KHC-Test road.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.05b
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• pp.41-45
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• 2005

In this paper, parameters of electron temperature and density for the mercury-free lighting-source were measured to diagnosis and analyze in Xe based inductively coupled plasma(ICP). In results at several dependences of 20~100 mTorr Xenon pressure, 50~200W RF power and horizontal distribution were especially mentioned. When Xe pressure was 20mTorr and RF power was 200W, the electron temperature and density were respectively 3.58eV and $3.56{\times}10^{12}cm^{-3}$. The key parameters of Xe based ICP depended on Xe pressure more than RF power that could be verified. A high electron temperature and low electron density with a suitable Xe pressure are indispensible parameters for Xe based ICP lighting-source.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2418-2420
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• 2005

In this paper, parameters of electron temperature and density for the mercury-free lighting-source were measured to diagnosis and analyze in Xe based inductively coupled plasma(ICP). In results at several dependences of $20{\sim}100mTorr$ Xenon pressure, $50{\sim}200W$ RF power and horizontal distribution were especially mentioned. When Xe pressure was 20mTorr and RF power was 200W, the electron temperature and density were respectively 3.58eV and $3.56{\times}10^{12}cm^{-3}$. The key parameters of Xe based ICP depended on Xe pressure more than RF power that could be verified. A high electron temperature and low electron density with a suitable Xe pressure are indispensible parameters for Xe based ICP lighting-source.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.12a
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• pp.43-47
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• 2006

In this paper, parameters of electron temperature and density for the mercury-free lighting-source were measured to diagnosis and analyze in Xe based inductively coupled plasma (ICP). As results at several dependences of 20~100mTorr Xenon pressure, the brightness of discharge tube was higher (4,900 $cd/m^2$) than other conditions when Xe pressure was 20mTorr and RF power was 200W. In that case, the electron temperature and density were 3.58eV and $3.56{\times}10^{12}cm^2$, respectively. The key parameters of Xe based ICP depended on Xe pressure more than RF power that could be verified. A high electron temperature and low electron density with a suitable Xe pressure are indispensible parameters for Xe based ICP lighting-source.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1248-1259
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• 2016

Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.

• Korean Journal of Radiology
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• v.24 no.9
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• pp.849-859
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• 2023

Objective: The prognostic value of the volume and density of skeletal muscles in the abdominal waist of patients with colon cancer remains unclear. This study aimed to investigate the association between the automated computed tomography (CT)-based volume and density of the muscle in the abdominal waist and survival outcomes in patients with colon cancer. Materials and Methods: We retrospectively evaluated 474 patients with colon cancer who underwent surgery with curative intent between January 2010 and October 2017. Volumetric skeletal muscle index and muscular density were measured at the abdominal waist using artificial intelligence (AI)-based volumetric segmentation of body composition on preoperative pre-contrast CT images. Patients were grouped based on their skeletal muscle index (sarcopenia vs. not) and muscular density (myosteatosis vs. not) values and combinations (normal, sarcopenia alone, myosteatosis alone, and combined sarcopenia and myosteatosis). Postsurgical disease-free survival (DFS) and overall survival (OS) were analyzed using univariable and multivariable analyses, including multivariable Cox proportional hazard regression. Results: Univariable analysis showed that DFS and OS were significantly worse for the sarcopenia group than for the non-sarcopenia group (P = 0.044 and P = 0.003, respectively, by log-rank test) and for the myosteatosis group than for the non-myosteatosis group (P < 0.001 by log-rank test for all). In the multivariable analysis, the myosteatotic muscle type was associated with worse DFS (adjusted hazard ratio [aHR], 1.89 [95% confidence interval, 1.25-2.86]; P = 0.003) and OS (aHR, 1.90 [95% confidence interval, 1.84-3.04]; P = 0.008) than the normal muscle type. The combined muscle type showed worse OS than the normal muscle type (aHR, 1.95 [95% confidence interval, 1.08-3.54]; P = 0.027). Conclusion: Preoperative volumetric sarcopenia and myosteatosis, automatically assessed from pre-contrast CT scans using AI-based software, adversely affect survival outcomes in patients with colon cancer.

• 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 the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.36-42
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• 2010

This paper presents a hybrid approach to the construction of quasi-cyclic (QC) low-density parity-check (LDPC) codes based on parallel bundles in Euclidean geometries and circulant permutation matrices. Codes constructed by this method are shown to be regular with large girth and low density. Simulation results show that these codes perform very well with iterative decoding and achieve reasonably large coding gains over uncoded system.