• Title/Summary/Keyword: KERNEL

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Enhancing Kernel Module Security Using WebAssembly (웹어셈블리를 활용한 커널 모듈 보안성 강화)

  • Hajeong Lim;Hojoon Lee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.337-344
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    • 2023
  • Modern OSs, including Linux, show high scalability by adopting a monolithic kernel design, but have weak security because they share all memory space. This study presents a kernel module that are isolated inside the kernel using WebAssembly. WebAssembly provides a high-performance virtual machine by defining a low-level instruction set while guaranteeing memory safety. In this paper, the WebAssembly execution environment is implemented inside the kernel, allowing developers to control the operation of kernel modules and achieving higher security.

A Note on Deconvolution Estimators when Measurement Errors are Normal

  • Lee, Sung-Ho
    • Communications for Statistical Applications and Methods
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    • v.19 no.4
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    • pp.517-526
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    • 2012
  • In this paper a support vector method is proposed for use when the sample observations are contaminated by a normally distributed measurement error. The performance of deconvolution density estimators based on the support vector method is explored and compared with kernel density estimators by means of a simulation study. An interesting result was that for the estimation of kurtotic density, the support vector deconvolution estimator with a Gaussian kernel showed a better performance than the classical deconvolution kernel estimator.

On Predicting with Kernel Ridge Regression

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.103-111
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    • 2003
  • Kernel machines are used widely in real-world regression tasks. Kernel ridge regressions(KRR) and support vector machines(SVM) are typical kernel machines. Here, we focus on two types of KRR. One is inductive KRR. The other is transductive KRR. In this paper, we study how differently they work in the interpolation and extrapolation areas. Furthermore, we study prediction interval estimation method for KRR. This turns out to be a reliable and practical measure of prediction interval and is essential in real-world tasks.

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INTEGRAL KERNEL OPERATORS ON REGULAR GENERALIZED WHITE NOISE FUNCTIONS

  • Ji, Un-Cig
    • Bulletin of the Korean Mathematical Society
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    • v.37 no.3
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    • pp.601-618
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    • 2000
  • Let (and $g^*$) be the space of regular test (and generalized, resp.) white noise functions. The integral kernel operators acting on and transformation groups of operators on are studied, and then every integral kernel operator acting on can be extended to continuous linear operator on $g^*$. The existence and uniqueness of solutions of Cauchy problems associated with certain integral kernel operators with intial data in $g^*$ are investigated.

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THE GREEN FUNCTION AND THE SZEGŐ KERNEL FUNCTION

  • Chung, Young-Bok
    • Honam Mathematical Journal
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    • v.36 no.3
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    • pp.659-668
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    • 2014
  • In this paper, we express the Green function in terms of the classical kernel functions in potential theory. In particular, we obtain a formula relating the Green function and the Szegő kernel function which consists of only the Szegő kernel function in a $C^{\infty}$ smoothly bounded finitely connected domain in the complex plane.

Kernel Poisson regression for mixed input variables

  • Shim, Jooyong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1231-1239
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    • 2012
  • An estimating procedure is introduced for kernel Poisson regression when the input variables consist of numerical and categorical variables, which is based on the penalized negative log-likelihood and the component-wise product of two different types of kernel functions. The proposed procedure provides the estimates of the mean function of the response variables, where the canonical parameter is linearly and/or nonlinearly related to the input variables. Experimental results are then presented which indicate the performance of the proposed kernel Poisson regression.

Design of Virtualization of Operating Systems on L4 Kernel (L4 커널 기반에서 운영체제 가상화에 대한 설계)

  • Kim, Dong-Geun;Shin, Dong-Ryeol
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.659-660
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    • 2008
  • Virtualization of operating systems have already been developed and commercialized in the enterprise computing area. As the computing power of the embedded systems is growing, it is regarded that the virtualization is the important research area. The virtualization is typically established by the micro kernel. L4 kernel is the one example of the micro kernel. In this paper, we propose the architecture for virtualization of Linux over the L4 kernel.

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ALGEBRAIC KERNEL FUNCTIONS AND REPRESENTATION OF PLANAR DOMAINS

  • Jeong, Moon-Ja;Taniguchi, Masahiko
    • Journal of the Korean Mathematical Society
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    • v.40 no.3
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    • pp.447-460
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    • 2003
  • In this paper we study the non-degenerate n-connected canonical domains with n>1 related to the conjecture of S. Bell in [4]. They are connected to the algebraic property of the Bergman kernel and the Szego kernel. We characterize the non-degenerate doubly connected canonical domains.

A NEW BIHARMONIC KERNEL FOR THE UPPER HALF PLANE

  • Abkar, Ali
    • Journal of the Korean Mathematical Society
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    • v.43 no.6
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    • pp.1169-1181
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    • 2006
  • We introduce a new biharmonic kernel for the upper half plane, and then study the properties of its relevant potentials, such as the convergence in the mean and the boundary behavior. Among other things, we shall see that Fatou's theorem is valid for these potentials, so that the biharmonic Poisson kernel resembles the usual Poisson kernel for the upper half plane.