• Title/Summary/Keyword: density-based

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Estimation of the Lubricating Oil Rheology at High Pressure Based on Phase Diagram

  • Rahman, Md.Z.;Ohno, N.
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 2002.10b
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    • pp.85-86
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    • 2002
  • For rheology investigation of lubricating oils, first phase diagrams were made from determined free volume based on density measurements and the temperature-pressure relation was estimated using the expansion coefficient of free volume and the temperature-pressure relation of the viscoelastic transition point. Next, the authors proposed the density-pressure-temperature relation and the viscosity-pressure-temperature relation of the tested oils based on the free volume and the phase diagrams. Moreover, it was shown that the Ehrenfest equation or the gradient of the phase diagram is closely related to the expansion coefficient of free volume.

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Detection of Abnormal Region of Skin using Gabor Filter and Density-based Spatial Clustering of Applications with Noise (가버 필터와 밀도 기반 공간 클러스터링을 이용한 피부의 이상 영역 검출)

  • Jeon, Minseong;Cheoi, Kyungjoo
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.117-129
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    • 2018
  • In this paper, we suggest a new system that detects abnormal region of skim. First, an illumination elimination algorithm which uses LAB color model is processed on input facial image to obtain robust facial image for illumination, and then gabor filter is processed to detect the reactivity of discontinuity. And last, the density-based spatial clustering of applications with noise(DBSCAN) algorithm is processed to classify areas of wrinkles, dots, and other skin diseases. This method allows the user to check the skin condition of the images taken in real life.

A Lattice Model Based Molecular Clusters for Supercritical Fluids (초임계 유체를 위한 분자 클러스터 기반의 격자모델)

  • Shin, Moon-Sam
    • Proceedings of the KAIS Fall Conference
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    • 2011.05a
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    • pp.306-309
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    • 2011
  • A lattice model based molecular clusters is presented to improve a classical equation of state(EOS) for volumetric properties in the critical region. The term is based on the two assumptions: (1) The Helmholtz energy is individually divided into classical and long-range density fluctuation contribution (2) All molecules form cluster near the critical region due to long-range density fluctuation. To formulate such molecular cluster, we extended the Veytsman statistics originally developed for the cluster due to hydrogen bonding. The probability function in the statistics is modified to represent the characteristics of long-range density fluctuation vanishing far from critical region. The proposed fluctuation contribution was incorporated into the Sanchez-Lacombe EOS and the combined model with 6 adjustable parameters has been tested against experimental VLE data for pure compounds. The combined model is found to well represent flatten critical isotherm for methane and top of the coexistence curve for the tested components.

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Performance Improvement of Iterative Demodulation and Decoding for Spatially Coupling Data Transmission by Joint Sparse Graph

  • Liu, Zhengxuan;Kang, Guixia;Si, Zhongwei;Zhang, Ningbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5401-5421
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    • 2016
  • Both low-density parity-check (LDPC) codes and the multiple access technique of spatially coupling data transmission (SCDT) can be expressed in bipartite graphs. To improve the performance of iterative demodulation and decoding for SCDT, a novel joint sparse graph (JSG) with SCDT and LDPC codes is constructed. Based on the JSG, an approach for iterative joint demodulation and decoding by belief propagation (BP) is presented as an exploration of the flooding schedule, and based on BP, density evolution equations are derived to analyze the performance of the iterative receiver. To accelerate the convergence speed and reduce the complexity of joint demodulation and decoding, a novel serial schedule is proposed. Numerical results show that the joint demodulation and decoding for SCDT based on JSG can significantly improve the system's performance, while roughly half of the iterations can be saved by using the proposed serial schedule.

An Optical-Density-Based Feedback Feeding Method for Ammonium Concentration Control in Spirulina platensis Cultivation

  • Bao, Yilu;Wen, Shumei;Cong, Wei;Wu, Xia;Ning, Zhengxiang
    • Journal of Microbiology and Biotechnology
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    • v.22 no.7
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    • pp.967-974
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    • 2012
  • Cultivation of Spirulina platensis using ammonium salts or wastewater containing ammonium as alternative nitrogen sources is considered as a commercial way to reduce the production cost. In this research, by analyzing the relationship between biomass production and ammonium-N consumption in the fed-batch culture of Spirulina platensis using ammonium bicarbonate as a nitrogen nutrient source, an online adaptive control strategy based on optical density (OD) measurements for controlling ammonium feeding was presented. The ammonium concentration was successfully controlled between the cell growth inhibitory and limiting concentrations using this OD-based feedback feeding method. As a result, the maximum biomass concentration (2.98 g/l), productivity (0.237 g/l d), nitrogen-to-cell conversion factor (7.32 gX/gN), and contents of protein (64.1%) and chlorophyll (13.4mg/g) obtained by using the OD-based feedback feeding method were higher than those using the constant and variable feeding methods. The OD-based feedback feeding method could be recognized as an applicable way to control ammonium feeding and a benefit for Spirulina platensis cultivations.

Effect of Improving Accuracy for Effective Atomic number (EAN) and Relative Electron Density (RED) extracted with Polynomial-based Calibration in Dual-energy CT

  • Daehong Kim;Il-Hoon Cho;Mi-jo Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.7
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    • pp.1017-1023
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    • 2023
  • The purpose of this study was to improve the accuracy of effective atomic number (EAN) and relative electron density (RED) using a polynomial-based calibration method using dual-energy CT images. A phantom composed of 11 tissue-equivalent materials was acquired with dual-energy CT to obtain low- and high-energy images. Using the acquired dual-energy images, the ratio of attenuation of low- and high-energy images for EAN was calibrated based on Stoichiometric, Quadratic, Cubic, Quartic polynomials. EAN and RED were extracted using each calibration method. As a result of the experiment, the average error of EAN using Cubic polynomial-based calibration was minimum. Even in the RED image extracted using EAN, the error of the Cubic polynomial-based RED was minimum. Cubic polynomial-based calibration contributes to improving the accuracy of EAN and RED, and would like to contribute to accurate diagnosis of lesions in CT examinations or quantification of various materials in the human body.

Main Content Extraction from Web Pages Based on Node Characteristics

  • Liu, Qingtang;Shao, Mingbo;Wu, Linjing;Zhao, Gang;Fan, Guilin;Li, Jun
    • Journal of Computing Science and Engineering
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    • v.11 no.2
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    • pp.39-48
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    • 2017
  • Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.

Differences in Network-Based Kernel Density Estimation According to Pedestrian Network and Road Centerline Network

  • Lee, Byoungkil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.5
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    • pp.335-341
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    • 2018
  • The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

Visualizing Cluster Hierarchy Using Hierarchy Generation Framework (계층 발생 프레임워크를 이용한 군집 계층 시각화)

  • Shin, DongHwa;L'Yi, Sehi;Seo, Jinwook
    • KIISE Transactions on Computing Practices
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    • v.21 no.6
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    • pp.436-441
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    • 2015
  • There are many types of clustering algorithms such as centroid, hierarchical, or density-based methods. Each algorithm has unique data grouping principles, which creates different varieties of clusters. Ordering Points To Identify the Clustering Structure (OPTICS) is a well-known density-based algorithm to analyze arbitrary shaped and varying density clusters, but the obtained clusters only correlate loosely. Hierarchical agglomerative clustering (HAC) reveals a hierarchical structure of clusters, but is unable to clearly find non-convex shaped clusters. In this paper, we provide a novel hierarchy generation framework and application which can aid users by combining the advantages of the two clustering methods.

Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method (크리깅 근사모델 기반의 중요도 추출법을 이용한 고장확률 계산 방안)

  • Lee, Seunggyu;Kim, Jae Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.5
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    • pp.381-389
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    • 2017
  • The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.