• Title/Summary/Keyword: Density based Method

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An Incident Detection Method for Using Speed-Density Relations (검지기간 속도-밀도의 관계를 활용한 돌발상황 감지기법)

  • Lee, Seon-Ha;An, U-Yeong;Gang, Hui-Chan
    • Journal of Korean Society of Transportation
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    • v.24 no.2 s.88
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    • pp.127-137
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    • 2006
  • This Paper Presents a novel incident detection method for using the speed-density difference between detectors. When a incident is happened the downstream traffic condition is mostly lower speed and higher density and the upstream is higher speed and lower density In respect of such characteristics, we can suggest a method for detecting an incident based on the speed-density information provided from detectors. The incident detection method is tested by using the accident data collected from the Cheonan-Nonsan Highway. The results show that suck an incident detection method can analyze the position of accident by comparing the speed-density difference between detectors. The work described in this paper is only at on early stage, in the sense that there are several areas to be further investigated in application of this method. such as setting a critical value for judging the incident. a level of accident wave, a varying Pattern between the incident locations and detectors, etc.

Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation

  • Yee, Jaeyong;Park, Taesung;Park, Mira
    • Genomics & Informatics
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    • v.20 no.2
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    • pp.17.1-17.11
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    • 2022
  • Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

Application of Fuzzy Information Representation Using Frequency Ratio and Non-parametric Density Estimation to Multi-source Spatial Data Fusion for Landslide Hazard Mapping

  • Park No-Wook;Chi Kwang-Hoon;Kwon Byung-Doo
    • Journal of the Korean earth science society
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    • v.26 no.2
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    • pp.114-128
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    • 2005
  • Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

Estimation of Non-Gaussian Probability Density by Dynamic Bayesian Networks

  • Cho, Hyun-C.;Fadali, Sami M.;Lee, Kwon-S.
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.408-413
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    • 2005
  • A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

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An Improved Automated Spectral Clustering Algorithm

  • Xiaodan Lv
    • Journal of Information Processing Systems
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    • v.20 no.2
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    • pp.185-199
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    • 2024
  • In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

Estimation of the Moisture Content of Wood by Density - Moisture Variation with Annual Ring Width - (목재의 밀도에 의한 함수율 추정 - 연륜폭에 따른 변이 -)

  • Hwang, Kweon-Hwan;Lee, Weon-Hee
    • Journal of the Korean Wood Science and Technology
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    • v.23 no.3
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    • pp.58-65
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    • 1995
  • The possibilities of the estimation of the moisture content(MC) for sitka-spruce (Picea sitchensis Carr.) by measuring density have been investigated. The method is based on the relationships between the wood density and moisture content of wood expressed by Equations (8)~(9). The purpose of this study is examining the estimation of the moisture content of wood by density and the variation of moisture content with annual ring width of wood. The following conclusions were obtained; 1. This method is very convenience because of the average moisture content of wood can be obtained by a simple estimation. This estimation can be made from the easy measurement of the weight and volume of wood. 2. Coefficient of determination between the experimental MCs and theoretical MCs which is calculated by the oven-dry densities of each specimens and Equations (8), (9) is 0.98. This Correlation is very remarkable. Therefore the model Equations on the estimation of moisture content by wood density was available. 3. Relationship between experimental MCs and theoretical MCs which is estimated by average oven-dry density of total specimens showed positive correlation(Fig.2). But from the Fig.4. we can concluded that the number of specimens is two groups. This phenomenon is considered that the variation of MC by the annual ring width from the specimens' observations. Consequently, the MCs of wood by density, is likely to be successful method. can be estimate using by the average oven-dry densities divided with the annual ring widths of wood.

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Measurement of Electron Density and Electron-neutral Collision Frequency Using Cutoff Probe Based on the Plasma Reactance Measurement

  • Yu, Gwang-Ho;Kim, Dae-Ung;Na, Byeong-Geun;Seo, Byeong-Hun;Yu, Sin-Jae;Kim, Jeong-Hyeong;Seong, Dae-Jin;Sin, Yong-Hyeon;Jang, Hong-Yeong
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.184-184
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    • 2012
  • We proposed a new measurement method of cutoff probe using the reactance spectrum of the plasma in cutoff probe system instead of transmission spectrum. The high accurate reactance spectrum of the plasma which is expected in previous circuit simulation of cutoff probe [1] was measured by using the automatic port extension method of the network analyzer. The measured reactance spectrum is good agreement with E/M wave simulation result (CST Microwave Studio). From the analysis of the measured reactance spectrum based on the circuit modeling, not only the electron density but also electron-neutral collision frequency can be simply obtained. The obtained results of electron density and e-n collision frequency were presented and discussed in wide range of experimental conditions, together with comparison result with previous methods (a previous cutoff probe using transmission spectrum and a single langmuir probe).

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Design of High Power Density AC/DC Adapter (고전력밀도 AC/DC 어댑터의 설계)

  • Lee, Jun-Young
    • The Transactions of the Korean Institute of Power Electronics
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    • v.15 no.4
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    • pp.259-265
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    • 2010
  • The proposed method offers an improved control method for high power density AC/DC adapter by using more energy efficient electrical equipments. Power factor corrector (PFC) topology is based on boost topology with boundary conduction mode (BCM) and DC/DC topology is based on LLC resonant converter, which helps to reduce size of the semiconductor and the magnetic devices. Test results with 85W AC/DC adapter (18.5V/4.6A) design shows that the measured efficiency is 90% at $90V_{rms}$ input voltage with power density of $36W/in^3$. It also shows low no load power consumption of about 0.5W.

Comparison of Estimation Methods for the Density on Expressways Using Vehicular Trajectory Data from a Radar Detector (레이더검지기의 차량궤적 정보기반의 고속도로 밀도산출방법에 관한 비교)

  • Kim, Sang-Gu;Han, Eum;Lee, Hwan-Pil;Kim, Hae;Yun, Ilsoo
    • International Journal of Highway Engineering
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    • v.18 no.5
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    • pp.117-125
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    • 2016
  • PURPOSES : The density in uninterrupted traffic flow facilities plays an important role in representing the current status of traffic flow. For example, the density is used for the primary measures of effectiveness in the capacity analysis for freeway facilities. Therefore, the estimation of density has been a long and tough task for traffic engineers for a long time. This study was initiated to evaluate the performance of density values that were estimated using VDS data and two traditional methods, including a method using traffic flow theory and another method using occupancy by comparing the density values estimated using vehicular trajectory data generated from a radar detector. METHODS : In this study, a radar detector which can generate very accurate vehicular trajectory within the range of 250 m on the Joongbu expressway near to Dongseoul tollgate, where two VDS were already installed. The first task was to estimate densities using different data and methods. Thus, the density values were estimated using two traditional methods and the VDS data on the Joongbu expressway. The density values were compared with those estimated using the vehicular trajectory data in order to evaluate the quality of density estimation. Then, the relationship between the space mean speed and density were drawn using two sets of densities and speeds based on the VDS data and one set of those using the radar detector data. CONCLUSIONS : As a result, the three sets of density showed minor differences when the density values were under 20 vehicles per km per lane. However, as the density values become greater than 20 vehicles per km per lane, the three methods showed a significant difference among on another. The density using the vehicular trajectory data showed the lowest values in general. Based on the in-depth study, it was found out that the space mean speed plays a critical role in the calculation of density. The speed estimated from the VDS data was higher than that from the radar detector. In order to validate the difference in the speed data, the traffic flow models using the relationships between the space mean speed and the density were carefully examined in this study. Conclusively, the traffic flow models generated using the radar data seems to be more realistic.

Finite Element Modeling of Low Density Polyurethane Foam Material (저밀도 폴리우레탄 포옴재료의 유한요소 모델링)

  • 김원택;최형연
    • Transactions of the Korean Society of Automotive Engineers
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    • v.4 no.2
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    • pp.183-188
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    • 1996
  • The compressive stress-strain response of Low Density Polyurethane foam material is modeled using the finite element method. A constitutive equation which include experimental constants based on quasi-static and dynamic uniaxial compression test is proposed. Impact test with different impactor masses and velocities are performed to verify the proposed model. The comparison between impact test and finite element analysis shows good agreements.

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