• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.1-9
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• 2019

This paper presents three potential risks in an environment that simultaneously performs the garbage collection and wear leveling in NAND flash memory. These risks may not only disturb the lifespan improvement of NAND flash memory, but also impose an additional overhead of page migrations. In this paper, we analyze the interference of garbage collection and wear leveling and we also provide two theoretical considerations for lifespan prolongation of NAND flash memory. To prove two solutions of three risks, we construct a simulation, based on DiskSim 4.0 and confirm realistic impacts of three risks in NAND flash memory. In experimental results, we found negative impacts of three risks and confirmed the necessity for a coordinator module between garbage collection and wear leveling for reducing the overhead and prolonging the lifespan of NAND flash memory.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.35-44
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• 2011

Memory errors can cause not only program malfunctions but also even unexpected system halt. Though a programmer checks memory errors, some memory errors with low occurrence frequency are missed to detect. In this paper, we propose a method for effectively detecting such memory errors using instruction transition diagrams through analyzing assembly codes obtained by disassembling an executable file. Out of various memory errors, local memory return errors, null pointer access errors and uninitialized pointer access errors are targeted for detection. When applying the proposed method to various programs including well-known open source programs such as Apache web server and PHP script interpreter, some potential memory errors are detected.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2010.05a
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• pp.37-41
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• 2010

The previous investigations of electroencephalogram (EEG) activity in the memory retrieval tasks demonstrated that event-related potentials (ERP) during recollection showed different durations and the peak levels from those without recollection. However, it has been unknown that recollection in memory retrieval also modulates high-frequency brain rhythms as well as establishes large-scale synchronization across different cortical areas. In this study, we examined the spectral components of the EEG signals, especially the gamma bands (20-80Hz), measured during the memory retrieval tasks. Specifically, we focused on two major spectral components: first, we evaluated the temporal patterns of the power spectral density before and after the onset of the memory retrieval task; second, we estimated phase synchrony between all possible pairs of EEG channels to evaluate large-scale synchronization. Fourteen healthy subjects performed the memory retrieval task in the virtual reality environment where they selected whether or not t he present item was seen in the previous training period. When the subjects viewed the unseen items, the middle gamma power (40-60Hz) appeared to increase 200-500ms after stimulus onset while the low gamma power (20Hz) was suppressed all the way through the post-stimulus period 150ms after onset. The degree of phase synchronization in this low gamma level, however, increased when the subjects fetched the item from memory. This suggests that phase synchrony analysis might reveal different aspects of the memory retrieval process than the gamma power, providing additional information to the inference on the brain dynamics during memory retrieval.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1179-1187
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• 2016

Through the rapid development of latest hardware technology, high performance as well as miniaturized size is the essentials of embedded system to meet various requirements from the society. It raises possibilities of genuine realization of IoT environment whose size and battery must be considered. However, the limitation of battery persistency and capacity restricts the long battery life time for guaranteeing real-time system. To maximize battery life time, low power technology which lowers the power consumption should be highly required. Previous researches mostly highlighted improving one single type of memory to increase ones efficiency. In this paper, reversely, considering multiple memories to optimize whole memory system is the following step for the efficient low power embedded system. Regarding to that fact, this paper suggests the study of volatile memory, whose capacity is relatively smaller but much low-powered, and non-volatile memory, which do not consume any standby power to keep data, to maximize the efficiency of the system. By executing function in specific memories, non-volatile and volatile memory, the quantitative analysis of power consumption is progressed. In spite of the opportunity cost of all of theses extra works to locate function in volatile memory, higher efficiencies of both power and energy are clearly identified compared to operating single non-volatile memory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.655-658
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• 2016

Xilinx 7-Series FPGA(Field Programmable Gate Array)s mainly used for the implementation of high-performance digital circuit have SRAM-type configuration memory and can malfunction when soft errors occur in their configuration memory. SEM(Soft Error Mitigation Controller) offered by Xilinx helps users mitigate the influence of soft errors in configuration memory. When soft errors occur, SEM Controller can recover the state of FPGA through partial reconfiguration if the soft errors are correctable by ECC(Error Correction Code) and CRC(Cyclic Redundancy Code). This paper presents the availability analysis of Xilinx 7-Series FPGAs against soft errors under the protection of the SEM Controller. Availability functions are derived and compared according to the correction capability of the SEM Controller. The result may help to estimate the reliability of SRAM-based FPGA running in an environment where soft errors may occur.

• Korean Journal of Adult Nursing
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• v.12 no.1
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• pp.17-29
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• 2000

The purpose of this study is to find out the effects of depression on older adults' metamemory and memory performances. The subjects of the study consisted of 103 older adults over the age of 60 who are living in Kangwon Province. Some data were collected by means of the interview method, using questionnaires for metamemory (MIA questionnaire by Hultsch, et al., 1988), and depression(GDS by Yesavage and Sheikl, 1986). Other data were collected by a testing method on the memory performance, such as the immediate word recall task, the delayed word recall task, the word recognition task(Elderly Verbal Learning Test by Kyung Mi Choi, 1998), and the face recognition task(Face Recognition Task tool developed by this study). The results of this study were as follows: 1) The average point of depressed older persons' metamemory is 3.2 on a 5 point scale and was significantly lower than nondepressed older persons' point of 3.6. Looking into each sub-concept of metamemory, depressed persons' points are higher in terms of task(4.1), but are lower in terms of change(2.3), locus(2.6), and strategy(2.9) in comparison with nondepressed persons' points. 2) Depressed older persons' memory performances are all significantly lower than nondepressed person's, especially in terms of face recognition task(t=7.26, p<.0082) and word recognition task(t=6.58, p<.01). 3) In both depressed and nondepressed persons, metamemory has a close correlation with all memory tasks. In particular, depressed older persons' correlation is higher across the board, especially in memory self-efficacy of metamemory(r=.36 - .49) in comparison with nondepressed persons. 4) According to the results of analysis on the relations between metamemory and memory performances of each memory task using canonical analysis, in the case of depressed older persons, strategy, locus, capability and task have high correlation with word recognition task and delayed word recall task. Also in the case of nondepressed persons, achievement, strategy, change and locus variable have high correlation with face recognition task and immediate word recall task. As mentioned above, depression variables have a negative effect on older persons' metamemory and memory performance. In conclusion, when we care for depressed older persons with less memory ability, we have to consider the outcomes of this study are relevant. In addition, it is necessary to develop nursing intervention in order to prevent memory loss and improve memory performance in depressed older persons.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.165-170
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• 2017

Many studies have utilized GPGPU (General-Purpose Graphic Processing Unit) and its high computing power to compute complex tasks. The characteristics of GPGPU programs necessitate the operations of memory copy between the host and device. A high latency period can affect the performance of the program. Thus, it is required to significantly improve the performance of GPGPU programs by optimizations. By executing multiple GPGPU programs simultaneously, the latency hiding effect of memory copy is achieved by overlapping the memory copy and computing operations in GPGPU. This paper presents the results of analyzing the latency hiding effect for memory copy operations. Furthermore, we propose a performance anticipation model and an algorithm for the limitations of using pinned memory, and show that the use of the proposed algorithm results in a 41% performance increase.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.393-398
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• 2007

In this paper, we propose the development of Artificial Hippocampus Algorithm(AHA) which remodels a principle of brain of hippocampus. Hippocampus takes charge auto-associative memory and controlling functions of long-term or short-term memory strengthening. We organize auto-associative memory based 4 steps system (EC, DG CA3, and CA1) and improve speed of teaming by addition of modulator to long-term memory teaming. In hippocampus system, according to the 3 steps order, information applies statistical deviation on Dentate Gyrus region and is labeled to responsive pattern by adjustment of a good impression. In CA3 region, pattern is reorganized by auto-associative memory. In CA1 region, convergence of connection weight which is used long-term memory is learned fast a by neural network which is applied modulator. To measure performance of Artificial Hippocampus Algorithm, PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis) are applied to face images which are classified by pose, expression and picture quality. Next, we calculate feature vectors and learn by AHA. Finally, we confirm cognitive rate. The results of experiments, we can compare a proposed method of other methods, and we can confirm that the proposed method is superior to the existing method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.71-82
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• 2011

Live data in physical memory can be acquired by live forensics but not by harddisk file-system analysis. Therefore, in case of forensic investigation, live forensics is widely used these days. But, existing live forensic methods, that use command line tools in live system, have many weaknesses; for instance, it is not easy to re-analyze and results can be modified by malicious code. For these reasons, in this paper we explain the Windows kernel architecture and how to analyze physical memory dump files to complement weaknesses of traditional live forensics. And then, we design and implement the Physical Memory Dump Explorer, and prove the effectiveness of our tool through test results.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.1-9
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• 2022

The purpose of this study is to examine the mediating effects of destination mood and tourist's mood state on the relationship between tourism memory and revisit intention focusing on the psychological approach. The number of subjects for the research is 301 visitors enjoying tourist destinations in Gyeongju and Jeju. This study employs path analysis offered by the AMOS 28 statistical program to analyze the mediating effects of destination mood and tourists' mood states. The path analysis shows that tourism experience positively influences tourism memory, tourism memory positively affects revisit intention, and there are mediating effects of Destination mood and tourist's mood state on the relationship between tourism memory and revisit intention.