• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.223-231
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• 2015

As smartphones support a variety of applications and their memory demand keeps increasing, the design of an efficient memory management policy is becoming increasingly important. Meanwhile, as nonvolatile memory (NVM) technologies such as PCM and STT-MRAM have emerged as new memory media of smartphones, characterizing memory references for NVM-based smartphone memory systems is needed. For the deep understanding of memory access features in smartphones, this paper performs comprehensive analysis of memory references for various smartphone applications. We first analyze the temporal locality and frequency of memory reference behaviors to quantify the effects of the two properties with respect to the re-reference likelihood of pages. We also analyze the skewed popularity of memory references and model it as a Zipf-like distribution. We expect that the result of this study will be a good guidance to design an efficient memory management policy for future smartphones.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.792-796
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• 2005

The methods of times series analysis have been recognized as important tools for assisting in solving problems related to the management of water resources. Especially, After more than 40 years the so-called Hurst effect remains an open problem in stochastic hydrology. Until now, its existence has been explained fly R/S analysis that roots in early work of the British hydrologist H.E. Hurst(1951). Today, the Hurst analysis is mostly used for the hydrological studies for memory and characteristics of time series and many methodologies have been developed for the analysis. So, there are many different techniques for the estimation of the Hurst exponent(H). However, the techniques can produce different characteristics for the persistence of a time series each other. We found that DFA is the most appropriate technique for the Hurst exponent estimation for both the shot term memory and long term memory. We analyze the SOI(Southern Oscillations Index) and 6 tree-ring series for USA sites by means of DFA and the BDS statistic is used for nonlinearity test of the series. From the results, we found that SOI series is nonlinear time series which has a long term memory of H=0.92. Contrary to earlier work of Rao(1999), all the tree- ring series are not random from our analysis. A certain tree ring series show a long term memory of H=0.97 and nonlinear property. Therefore, we can say that the SOI and tree-ring series may show long memory and nonlinearity.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.2
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• pp.72-78
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• 2002

Thermomechanical behavior and mechanical properties of A16061 matrix composite with shape memory alloy(SMA) fiber are studied by using fnite element analysis(FEA). The smartness of the SMA is given due to the shape memory effect of the TiNi fiber which generates compressive residual stress in the matrix material when healed after being prestrained. In this paper, an analytical model is assumed two dimentional axisymetric model of one fiber and around the matrix. To evaluate the strength of composite usig FEM, the concept of smart composite was simulated on computer. The Shape memory effect(SME) simulation is very difficult using FEM because of the nonlinear analysis and the elastic plastic analysis. Thus, in this paper, the FEA was carried out at two critical temperature conditions; room temperature and high temperature(363K). The analysis is compare the finite element analysis result with the test result for the analysis validity.

• Computational Structural Engineering
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• v.4 no.2
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• pp.103-110
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• 1991

To solve the large problems with limited core memory of computer, a disk management scheme called virtual memory database has been developed. Utilizing this technique along with memory moving scheme, an efficient in-and out-of-core column solver for the sparse symmetric matrix commonly arising in the finite element analysis is developed. Compared with other methods the algorithm is simple, therefore the coding and computational efficiencies are greatly enhanced. Analysis example shows that the proposed method efficiently solve the large structural problem on the small-memory micro-computer.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.34-39
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• 1990

For the analysis of structures, specifically if it is large-scale, in which case it can not be solved within the core memory, the majority of computation time is consumed In the solution of simultaneous linear equation. In this study an efficient in- and out-of-core column solver for sparse symmetric matrix utilizing memory moving scheme is developed. Compare with existing blocking methods the algorithm is simple, therefore the coding and computational efficiencies are greatly enhanced. Upon available memory size, the solver automatically performs solution within the core or outside core. Analysis example shows that the proposed method efficiently solve the large structural problem on the small-memory microcomputer.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.167-168
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• 2007

Design Rule이 작아짐에 따라 Transistor performance 향상을 위한 여러 방안중 SEG 공정이 적용되고 있으며 이에 따른 Transistor 특성 연구 결과이다. SEG공정 적용시 SEG Profile에 따라 Transistor의 Short Channel Effect 열화가 발생하였고 그 원인은 Sidewall Facet발생으로 추정되며 이를 개선시 Tr 특성이 개선됨을 확인하였다.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.90-94
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• 2020

Artificial intelligence (AI) is software that learns large amounts of data and provides the desired results for certain patterns. In other words, learning a large amount of data is very important, and the role of memory in terms of computing systems is important. Massive data means wider bandwidth, and the design of the memory system that can provide it becomes even more important. Providing wide bandwidth in AI systems is also related to power consumption. AlphaGo, for example, consumes 170 kW of power using 1202 CPUs and 176 GPUs. Since more than 50% of the consumption of memory is usually used by system chips, a lot of investment is being made in memory technology for AI chips. MRAM, PRAM, ReRAM and Hybrid RAM are mainly studied. This study presents various memory technologies that are being studied in artificial intelligence chip design. Especially, MRAM and PRAM are commerciallized for the next generation memory. They have two significant advantages that are ultra low power consumption and nearly zero leakage power. This paper describes a comparative analysis of the four representative new memory technologies.

• Journal of IKEEE
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• v.21 no.4
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• pp.353-357
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• 2017

In order to maintain numerous server systems used in enterprise and data center environments, the most important thing is to prevent the occurrence of UE (Uncorrectable Error) of each server system. With the recent development of cloud services, more memory modules are being used than ever before, while the operating frequency of server systems has increased and the process of developing memory has continued to shrink, making it more likely to fail. In these environments, there is a way to repair memory defects directly in the server system, but there is no currently available guideline to use it effectively. In this paper, we propose a method to effectively prevent memory failure in a server system based on the observation and analysis of memory failure phenomenon in existing system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.1
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• pp.87-96
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• 2006

In this paper, we examine general digital evidence collection process which is according to RFC3227 document[l], and establish specific steps for memory information collection. Besides, we include memory dump process to existing digital evidence collection process, and examine privacy information through dumping real user's memory and collecting pagefile which is part of virtual memory system. Especially, we discovered sensitive data which is like password and userID that exist in the half of pagefiles. Moreover, we suggest each analysis technique and computer forensic process for memory information and virtual memory.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.661-674
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• 2021

Malware, such as a rootkit that modifies the kernel, can adversely affect the analyst's judgment, making the analysis difficult or impossible if a mechanism to evade memory analysis is added. Therefore, we plan to preemptively respond to malware such as rootkits that bypass detection through advanced kernel modulation in the future. To this end, the main structure used in the Windows kernel was analyzed from the attacker's point of view, and a method capable of modulating the kernel object was applied to modulate the memory dump file. The result of tampering is confirmed through experimentation that it cannot be detected by memory analysis tool widely used worldwide. Then, from the analyst's point of view, using the concept of tamper resistance, it is made in the form of software that can detect tampering and shows that it is possible to detect areas that are not detected by existing memory analysis tools. Through this study, it is judged that it is meaningful in that it preemptively attempted to modulate the kernel area and derived insights to enable precise analysis. However, there is a limitation in that the necessary detection rules need to be manually created in software implementation for precise analysis.