• Title/Summary/Keyword: Kernel Space

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A new surrogate method for the neutron kinetics calculation of nuclear reactor core transients

  • Xiaoqi Li;Youqi Zheng;Xianan Du;Bowen Xiao
    • Nuclear Engineering and Technology
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    • v.56 no.9
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    • pp.3571-3584
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    • 2024
  • Reactor core transient calculation is very important for the reactor safety analysis, in which the kernel is neutron kinetics calculation by simulating the variation of neutron density or thermal power over time. Compared with the point kinetics method, the time-space neutron kinetics calculation can provide accurate variation of neutron density in both space and time domain. But it consumes a lot of resources. It is necessary to develop a surrogate model that can quickly obtain the temporal and spatial variation information of neutron density or power with acceptable calculation accuracy. This paper uses the time-varying characteristics of power to construct a time function, parameterizes the time-varying characteristics which contains the information about the spatial change of power. Thereby, the amount of targets to predict in the space domain is compressed. A surrogate method using the machine learning is proposed in this paper. In the construction of a neural network, the input is processed by a convolutional layer, followed by a fully connected layer or a deconvolution layer. For the problem of time sequence disturbance, a structure combining convolutional neural network and recurrent neural network is used. It is verified in the tests of a series of 1D, 2D and 3D reactor models. The predicted values obtained using the constructed neural network models in these tests are in good agreement with the reference values, showing the powerful potential of the surrogate models.

Training Sample and Feature Selection Methods for Pseudo Sample Neural Networks (의사 샘플 신경망에서 학습 샘플 및 특징 선택 기법)

  • Heo, Gyeongyong;Park, Choong-Shik;Lee, Chang-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.4
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    • pp.19-26
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    • 2013
  • Pseudo sample neural network (PSNN) is a variant of traditional neural network using pseudo samples to mitigate the local-optima-convergence problem when the size of training samples is small. PSNN can take advantage of the smoothed solution space through the use of pseudo samples. PSNN has a focus on the quantity problem in training, whereas, methods stressing the quality of training samples is presented in this paper to improve further the performance of PSNN. It is evident that typical samples and highly correlated features help in training. In this paper, therefore, kernel density estimation is used to select typical samples and correlation factor is introduced to select features, which can improve the performance of PSNN. Debris flow data set is used to demonstrate the usefulness of the proposed methods.

Classifying Windows Executables using API-based Information and Machine Learning (API 정보와 기계학습을 통한 윈도우 실행파일 분류)

  • Cho, DaeHee;Lim, Kyeonghwan;Cho, Seong-je;Han, Sangchul;Hwang, Young-sup
    • Journal of KIISE
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    • v.43 no.12
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    • pp.1325-1333
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    • 2016
  • Software classification has several applications such as copyright infringement detection, malware classification, and software automatic categorization in software repositories. It can be also employed by software filtering systems to prevent the transmission of illegal software. If illegal software is identified by measuring software similarity in software filtering systems, the average number of comparisons can be reduced by shrinking the search space. In this study, we focused on the classification of Windows executables using API call information and machine learning. We evaluated the classification performance of machine learning-based classifier according to the refinement method for API information and machine learning algorithm. The results showed that the classification success rate of SVM (Support Vector Machine) with PolyKernel was higher than other algorithms. Since the API call information can be extracted from binary executables and machine learning-based classifier can identify tampered executables, API call information and machine learning-based software classifiers are suitable for software filtering systems.

Analyzing the Overhead of the Memory Mapped File I/O for In-Memory File Systems (메모리 파일시스템에서 메모리 매핑을 이용한 파일 입출력의 오버헤드 분석)

  • Choi, Jungsik;Han, Hwansoo
    • KIISE Transactions on Computing Practices
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    • v.22 no.10
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    • pp.497-503
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    • 2016
  • Emerging next-generation storage technologies such as non-volatile memory will help eliminate almost all of the storage latency that has plagued previous storage devices. In conventional storage systems, the latency of slow storage devices dominates access latency; hence, software efficiency is not critical. With low-latency storage, software costs can quickly dominate memory latency. Hence, researchers have proposed the memory mapped file I/O to avoid the software overhead. Mapping a file into the user memory space enables users to access the file directly. Therefore, it is possible to avoid the complicated I/O stack. This minimizes the number of user/kernel mode switchings. In addition, there is no data copy between kernel and user areas. Despite of the benefits in the memory mapped file I/O, its overhead still needs to be addressed, as the existing mechanism for the memory mapped file I/O is designed for slow block devices. In this paper, we identify the overheads of the memory mapped file I/O via experiments.

HMM-based Upper-body Gesture Recognition for Virtual Playing Ground Interface (가상 놀이 공간 인터페이스를 위한 HMM 기반 상반신 제스처 인식)

  • Park, Jae-Wan;Oh, Chi-Min;Lee, Chil-Woo
    • The Journal of the Korea Contents Association
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    • v.10 no.8
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    • pp.11-17
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    • 2010
  • In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

출연(연)의 신기술개발 동향분석 연구

  • 이병민
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2003.05a
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    • pp.413-425
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    • 2003
  • Information Technology is the kernel technology deciding the industrial standard of one nation, and biotechnology will be the main technology of next generation. Based on this fact, a lot of efforts were made to industrialize them. Nano Technology is beginning to position itself as the kernel fusion technology, and its usage and popularity is expanding. Environmental and Energy Technology is a must-have strategic technology considering the increase demand of new energy development, the international environment correspondence, the environment-friendly production, and so forth. Space Technology is the field, which will contribute to raise the domestic component and system technology to the next level. In 2001, new technology research development costs total of 1 trillion 32 billion won in the following fields; 437.82 billion won in IT, 88.457 billion won in BT, 46.799 billion won in NT, 315.682 billion won in ET, and 112 billion won in ST. from component ratio, IT forms 42% which is the most, 31% for ET and in order of BT, ST and NT. ETRI and KISTI are concentrating on IT, KIBB is on BT, KAERI, KIER, KERI and KBSI are focusing on ET, and KIMM, KRISS, KRICT and KORDI is participating together in 4∼5 new technology such as IT, BT, NT and ET. Funds for research development costs in 5 new technology fields of 13 contribution (year) are consisted as follows; The Office for Government Policy Coordination has contributed 131 billion won (13%), 387 billion won (37%) by MOST, 256 billion won (25%) by Ministry of Information and Communication, 67 billion won (6%) by Ministry of Commerce, Industry and Energy, 19% by others and the industrial world. < Strategy for Technology Advancing > o Promotion of comprehensive contributing (year) new technology development research plan project o Increase research efficiency by promoting new technology development project connected with peculiar projects of organization by contribution (year) o Formation of superior research group by technology and introduction of operation system for research accumulation are needed. o Technology demand-oriented assignment deduction and promotion of research development project connected with intermediate long term objective o National will and investment extension of research development costs, training and popularization of professionals, commercialization promotion with efficient control for research plan and result.

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MTF Assessment and Image Restoration Technique for Post-Launch Calibration of DubaiSat-1 (DubaiSat-1의 발사 후 검보정을 위한 MTF 평가 및 영상복원 기법)

  • Hwang, Hyun-Deok;Park, Won-Kyu;Kwak, Sung-Hee
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.573-586
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    • 2011
  • The MTF(modulation transfer function) is one of parameters to evaluate the performance of imaging systems. Also, it can be used to restore information that is lost by a harsh space environment (radioactivity, extreme cold/heat condition and electromagnetic field etc.), atmospheric effects and falloff of system performance etc. This paper evaluated the MTF values of images taken by DubaiSat-1 satellite which was launched in 2009 by EIAST(Emirates Institute for Advanced Science and Technology) and Satrec Initiative. Generally, the MTF was assessed using various methods such as a point source method and a knife-edge method. This paper used the slanted-edge method. The slantededge method is the ISO 12233 standard for the MTF measurement of electronic still-picture cameras. The method is adapted to estimate the MTF values of line-scanning telescopes. After assessing the MTF, we performed the MTF compensation by generating a MTF convolution kernel based on the PSF(point spread function) with image denoising to enhance the image quality.

ON AN L-VERSION OF A PEXIDERIZED QUADRATIC FUNCTIONAL INEQUALITY

  • Chung, Jae-Young
    • Honam Mathematical Journal
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    • v.33 no.1
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    • pp.73-84
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    • 2011
  • Let f, g, h, k : $\mathbb{R}^n{\rightarrow}\mathbb{C}$ be locally integrable functions. We deal with the $L^{\infty}$-version of the Hyers-Ulam stability of the quadratic functional inequality and the Pexiderized quadratic functional inequality $${\parallel}f(x + y) + f(x - y) -2f(x) - 2f(y){\parallel}_{L^{\infty}(\mathbb{R}^n)}\leq\varepsilon$$ $${\parallel}f(x + y) + g(x - y) -2h(x) - 2f(y){\parallel}_{L^{\infty}(\mathbb{R}^n)}\leq\varepsilon$$ based on the concept of linear functionals on the space of smooth functions with compact support.

Color Space Conversion for Efficient Image Compression Using the DCT Kernel (효율적인 영상압축을 위한 DCT 커널 기반 컬러 좌표 변환)

  • Huh, Young-Min;Yoo, Hoon;Jeong, Je-Chang
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.693-696
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    • 2000
  • RGB 컬러 좌표계상에서는 각 컬러 성분간의 상관도가 매우 높고, 색을 표현할 때 R, G, B 각 성분에 똑같은 대역폭을 주기 때문에 영상의 압축 관점에서 효율적이지 못하다. 대표적인 영상압축 알고리즘인 MPEG-1,MPEG-2, MPEG-4, H.263, JPEG, JPEG-2000등에서는 압축 효율을 높이기 위해서 YCbCr 컬러 좌표계를 사용하고 있다. 본 논문에서는 좀 더 효율적인 영상 압축을 위해서 새로운 컬러 좌표계를 제안하고자 한다. 제안하는 컬러 좌표계는 DCT 커널에 기반을 두고 있다. DCT 컬러 좌표계는 각각의 커널끼리 직교하며, 빠른 연산이 가능하고, 구조가 간단하다. 실험결과, DCT 컬러 좌표계의 신호들의 분산이 YCbCr 컬러 좌표계의 신호들의 분산보다 작은 경향을 보이며, 동일한 비트율에서 작은 MSE (Mean Square Error)를 가지는 것을 실험적으로 알 수 있다.

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DEGENERATE VOLTERRA EQUATIONS IN BANACH SPACES

  • Favini, Angelo;Tanabe, Hiroki
    • Journal of the Korean Mathematical Society
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    • v.37 no.6
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    • pp.915-927
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    • 2000
  • This paper is concerned with degenerate Volterra equations Mu(t) + ∫(sub)0(sup)t k(t-s) Lu(s)ds = f(t) in Banach spaces both in the hyperbolic case, and the parabolic one. The key assumption is played by the representation of the underlying space X as a direct sum X = N(T) + R(T), where T is the bounded linear operator T = ML(sup)-1. Hyperbolicity means that the part T of T in R(T) is an abstract potential operator, i.e., -T(sup)-1 generates a C(sub)0-semigroup, and parabolicity means that -T(sup)-1 generates an analytic semigroup. A maximal regularity result is obtained for parabolic equations. We will also investigate the cases where the kernel k($.$) is degenerated or singular at t=0 using the results of Pruss[8] on analytic resolvents. Finally, we consider the case where $\lambda$ is a pole for ($\lambda$L + M)(sup)-1.

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