• Title/Summary/Keyword: Kernel Space

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Implementation of Secure Linux OS based on Kernel (커널 기반의 보안 리눅스 운영체제 구현)

  • 박태규;임연호
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.11 no.4
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    • pp.33-43
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    • 2001
  • This paper presents a secure Linux OS in which multi-level security functions are implemented at the kernel level. Current security efforts such as firewall or intrusion detection system provided in application-space without security features of the secure OS suffer from many vulnerabilities. However the development of the secure OS in Korea lies in just an initial state, and NSA has implemented a prototype of the secure Linux but published just some parts of the technologies. Thus our commercialized secure Linux OS with multi-level security kernel functions meets the minimum requirements for TCSEC B1 level as well kernel-mode encryption, real-time audit trail with DB, and restricted use of root privileges.

APPLICATIONS ON THE BESSEL-STRUVE-TYPE FOCK SPACE

  • Soltani, Fethi
    • Communications of the Korean Mathematical Society
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    • v.32 no.4
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    • pp.875-883
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    • 2017
  • In this work, we establish Heisenberg-type uncertainty principle for the Bessel-Struve Fock space ${\mathbb{F}}_{\nu}$ associated to the Airy operator $L_{\nu}$. Next, we give an application of the theory of extremal function and reproducing kernel of Hilbert space, to establish the extremal function associated to a bounded linear operator $T:{\mathbb{F}}_{\nu}{\rightarrow}H$, where H be a Hilbert space. Furthermore, we come up with some results regarding the extremal functions, when T are difference operators.

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.

EMBEDDING RIEMANNIAN MANIFOLDS VIA THEIR EIGENFUNCTIONS AND THEIR HEAT KERNEL

  • Abdalla, Hiba
    • Bulletin of the Korean Mathematical Society
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    • v.49 no.5
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    • pp.939-947
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    • 2012
  • In this paper, we give a generalization of the embeddings of Riemannian manifolds via their heat kernel and via a finite number of eigenfunctions. More precisely, we embed a family of Riemannian manifolds endowed with a time-dependent metric analytic in time into a Hilbert space via a finite number of eigenfunctions of the corresponding Laplacian. If furthermore the volume form on the manifold is constant with time, then we can construct an embedding with a complete eigenfunctions basis.

HOW TO SOLVE AN INFINITE SIMULTANEOUS SYSTEM OF QUADRATIC EQUATIONS

  • Chung, Phil Ung;Lin, Ying Zhen
    • Korean Journal of Mathematics
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    • v.13 no.2
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    • pp.275-284
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    • 2005
  • In the present paper we shall introduce several operators on the reproducing kernel spaces. And using them we shall find a solution of an infinite system of quadratic equations (1.1). In particular we shall convert problem for finding an approximate solution of infinite system of quadratic equations into problem for minimizing nonnegative biquadratic polynomial.

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Error Analysis in the Numerical Solution of Rayleigh Integral (Rayleigh 적분의 수치해에 관한 오차분석)

  • 이금원;김병기
    • Journal of Biomedical Engineering Research
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    • v.11 no.1
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    • pp.89-96
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    • 1990
  • The numerical evaluation of Rayleigh's integral for the sound source reconstruction can be speeded up by the use of angular frequency propagation method and the FFT. However, are several source of errors involved during the reconstruction. Besides the aliasing error due to undersampling in space, the wrap around error. which is caused by undersampling the kernel functionin frequency domain, and windowing effect are present. We found that there is no replicated source problem and the windowing effect is due to the windowing the kernel function In frequency domain, and, xero padding is always required to improve the quality of reconstruction.

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Divide and conquer kernel quantile regression for massive dataset (대용량 자료의 분석을 위한 분할정복 커널 분위수 회귀모형)

  • Bang, Sungwan;Kim, Jaeoh
    • The Korean Journal of Applied Statistics
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    • v.33 no.5
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    • pp.569-578
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    • 2020
  • By estimating conditional quantile functions of the response, quantile regression (QR) can provide comprehensive information of the relationship between the response and the predictors. In addition, kernel quantile regression (KQR) estimates a nonlinear conditional quantile function in reproducing kernel Hilbert spaces generated by a positive definite kernel function. However, it is infeasible to use the KQR in analysing a massive data due to the limitations of computer primary memory. We propose a divide and conquer based KQR (DC-KQR) method to overcome such a limitation. The proposed DC-KQR divides the entire data into a few subsets, then applies the KQR onto each subsets and derives a final estimator by aggregating all results from subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.