• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.1-8
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• 2017

In this paper, we propose a fault isolation system for device drivers of the Linux operating system. High availability systems impose stringent requirements upon Linux operating system. Especially device drivers can be a major source of operating system instability and many times contribute to system degradation and outages. The proposed fault isolation system identifies the occurrence of the memory-related faults in device driver and isolates it from the kernel. By operating at the early stage of the page fault handler in Linux kernel, the system detects which module causes fault and isolates it transparently from the remaining part of the kernel. By experiments, we show that the proposed system efficiently detects faults incurred by device driver, isolates the device driver and the process which accessed the driver module from the kernel.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.345-354
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• 2003

An incremental kernel principal component analysis(IKPCA) is proposed for the nonlinear feature extraction from the data. The problem of batch kernel principal component analysis(KPCA) is that the computation becomes prohibitive when the data set is large. Another problem is that, in order to update the eigenvectors with another data, the whole eigenvectors should be recomputed. IKPCA overcomes this problem by incrementally updating the eigenspace model. IKPCA is more efficient in memory requirement than a batch KPCA and can be easily improved by re-learning the data. In our experiments we show that IKPCA is comparable in performance to a batch KPCA for the classification problem on nonlinear data set.

• IE interfaces
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• v.23 no.3
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• pp.229-238
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• 2010

Virtual metrology (VM), a critical component of semiconductor manufacturing, is an efficient way of assessing the quality of wafers not actually measured. This is done based on a model between equipment sensor data (obtained for all wafers) and the quality characteristics of wafers actually measured. This paper considers principal component regression (PCR), partial least squares regression (PLSR), kernel PCR (KPCR), and kernel PLSR (KPLSR) as VM models. For each regression model, two cases are considered. One utilizes all explanatory variables in developing a model, and the other selects significant variables using the genetic algorithm (GA). The prediction performances of 8 regression models are compared for the short- and long-term etch process data. It is found among others that the GA-KPLSR model performs best for both types of data. Especially, its prediction ability is within the requirement for the short-term data implying that it can be used to implement VM for real etch processes.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.181-190
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• 2009

Module is an object file that can be loaded into operating system dynamically and has complete privileged access to all resources in kernel. Therefore trivial misuses in a module may cause critical system halts or deadlock situations. In this paper, we propose Kernel Resource Protector(KRP) scheme to reduce the various problems caused by module. KRP provides protections of a variety of kernel resources such as memory, major number and work queue resource. We implement the scheme onto linux kernel 2.6.18, and experimental results show that our scheme can protect kernel resources effectively.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.347-351
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• 1991

We propose a real time kernel chimera implemented under AT&T UNIX motorola versoin, Carnegie Mellon Univ. in U.S first developed chimera using SUN Worstation with Berkley UNIX based on VMEbus. The major differences between Canegie Mellon's and ours are downloading program and communication method between host and target. Original chimera used device driver but we used UNIX system call corresponding to shared memory when user downloads program and communicates. We modified kernel itself because the two different UNIX have different link editor.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.770-771
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• 2009

리눅스 커널을 VMM(Virtual Machine Monitor)로 만들어 주는 KVM의 메모리 관리 기법을 분석한다. Xen과의 차이점과 KVM의 구조를 알아보고 KVM에서의 메모리 관리 기법에 대해 분석하였다. 또한 CPU의 가상화 기능인 Intel VT-x가 어떻게 적용되었는지 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1448-1455
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• 2008

This paper designs Shared Memory on the Dual Core system so that it operates a general System V IPC on the Linux O.S. Shared Memory is the technique that many processes can access to identical memory area. We treat Shared Memory in this paper among big two branches of Shared Memory which are SVR in a kernel step format. We design a share memory facility of Linux operating system on the Dual Core System. In this paper the suggesting design plan of share memory facility in Dual Core system is enhancing the performance in existing unity processor system as a dual core practical use. We attempt a performance enhance in each CPU for each process which uses a share memory.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.777-778
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• 2006

In this thesis, we design and implement a Flash Cache Core Module (FCCM) which operates on the YAFFS NAND flash memory. The FCCM applies memory replacement policy and prefetching policy based on the page reference pattern of applications. Also, implement the Clean-First memory replacement technique considering the characteristics of flash memory. In this method the decision is made according to page hit to apply prefetched waiting area. The FCCM decrease I/O hit frequency up to 37%, Compared with the linux cache and prefetching policy. Also, it operated using less memory for prefetching(maximum 24% and average 16%) compared with the linux kernel.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.27-33
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• 2008

This paper designs Shared Memory on the Dual Core system so that it operates a general System V IPC on the Linux O.S. Shared Memory is the technique that many processes can access to identical memory area. We treat Shared Memory which is SVR in a kernel step. We design a share memory facility of Linux operating system on the Dual Core System. In this paper the suggesting of share memory facility design plan in Dual Core system is enhance the performance in existing an unity processor system as a dual core practical use. We attemp a performance enhance in each CPU for each process which uses a share memory.