• Journal of Digital Contents Society
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• v.14 no.1
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• pp.51-57
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• 2013

Storage device based on Flash Memory have many attractive features such as high performance, low power consumption, shock resistance, and low weight, so they replace HDDs to a certain extent. An Storage device based on Flash Memory has FTL(Flash Translation Layer) which emulate block storage devices like HDDs. A garbage collection, one of major functions of FTL, effects highly on the performance and the lifetime of devices. However, there is no de facto standard for new garbage collection algorithms. To solve this problem, we propose File Clustering Algorithm. File Clustering Algorithm respect to update page from same file at the same time. So, these are clustered to same block. For this mechanism, We propose Page Allocation Policy in FTL and use MIN-MAX GAP to guarantee wear leveling. To verify the algorithm in this paper, we use TPC Benchmark. So, The performance evaluation reveals that the proposed algorithm has comparable result with the existing algorithms(No wear leveling, Hot/Cold) and shows approximately 690% improvement in terms of the wear leveling.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.1-6
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• 2016

Purpose: Fluorine doped tin oxide (FTO) bottom electrode for $Ta_2O_5$ based RRAM was studied to apply for transparent resistive switching memory devices owing to its superior transparency, good conductivity and chemical stability. Methods: $ITO/Ta_2O_5/FTO$ (ITF) and $ITO/Ta_2O_5/Pt$ (ITP) devices were fabricated on glass and Si substrate, respectively. UV-visible (UV-VIS) spectroscopy was used to examine transparency of the ITF device and its band gap energy was determined by conventional Tauc plot. Electrical properties, such as electroforming and voltage-induced RS characteristics were measured and compared. Results: The device with an FTO bottom electrode showed good transparency (>80%), low forming voltage (~-2.5V), and reliable bipolar RS behavior. Whereas, the one with Pt electrode showed both bipolar and unipolar RS behaviors unstably with large forming voltage (~-6.5V). Conclusion: Transparent and conducting FTO can successfully realize a transparent RRAM device. It is concluded that FTO electrode may form a stable interface with $Ta_2O_5$ switching layer and plays as oxygen ion reservoir to supply oxygen vacancies, which eventually facilitates a stable operation of RRAM device.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.10 s.340
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• pp.1-8
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• 2005

In this paper, a FRAM design style based on PMOS-gating cell structure is described. The memory cell consists of a PMOS access transistor and a ferroelectric capacitor. Its plate is grounded. The proposed scheme employs three novel operating methods: 1) $V_{DD}$ precharged bitline, 2) negative-voltage wordline technique and 3) negative-pulse restore, Because this configuration doesn`t need the on-pitch plate control circuitry, it is effective in realizing cost-effective chip sizes. Implementation for a 2.5-V, 1-Mb FRAM prototype design in a $0.25-{\mu}m$, triple-well technology shows a chip size of $3.22\;mm^{2}$, an access time of 48 ns and an active current of 11 mA. The cell efficiency is 62.52 $\%$. It has gained approximately $20\;\%$ improvement in the cell array efficiency over the conventional plate-driven FRAM scheme.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.242-249
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• 2019

Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

• Journal of Oriental Neuropsychiatry
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• v.16 no.1
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• pp.119-128
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• 2005

Objective : The purpose of this study was to estimate the effects of Ramulus et Uncus Uncariae DM fraction on memory enhancing in rats Methods : We oral administered Ramulus et Uncus Uncariae DM fraction to rats then executed passive avoidance test and observed figure of pyramidal neuron on CA1 Results : Findings from our experiments have shown that REUD(>1mg/100g/ml) was effective in memorial improvement. and oral administration of REUD(100mg/100g/ml) for 2 weeks was found to induced the figure of pyramidal neuron on CA1 in rat hippocampus injured by scopolamine. Conclusions : As the result of this study, Decrease of memory induced by injection of scopolamine into rat was also attenuted by REUD, based on passive avoidance test, and REUD was found to reduce the activity of AChE and induced about the CA1 in rat hippocampus. Base on these findings, REUD may be beneficial for the treatment of AD.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.401-406
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• 2011

In order to solve a complex optimization problem more efficiently than traditional approaches, various meta-heuristic algorithms such as genetic algorithm, ant-colony algorithm, and harmony search algorithm have been extensively researched. Compared with other meta-heuristic algorithm, harmony search algorithm shows a better result to resolve the complex optimization issues. Harmony search algorithm is inspired by the improvision process of musician for most suitable harmony. In general, the performance of harmony search algorithm is determined by the value of harmony memory considering rate, and pitch adjust rate. In this paper, modified harmony search algorithm is proposed in order to derive best harmony. If the optimal solution of a specific problem can not be found for a certain period of time, a part of original harmony memory is updated as the selected suitable harmonies. Experimental results using test function demonstrate that the updated harmony memory can induce the approximation of reliable optimal solution in the short iteration, because of a few change of fitness.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.7-19
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• 2019

Ransomware is a malicious program that requires the cost of decryption after encrypting files on the user's desktop. Since the frequency and the financial damage of ransomware attacks are increasing each year, ransomware prevention, detection and recovery system are needed. Baek et al. proposed SSD-Insider, an algorithm for detecting ransomware within SSD. In this paper, we propose an AdvanSSD-Insider algorithm that substitutes a hash table used for the overwriting check with a bloom filter in the SSD-Insider. Experimental results show that the AdvanSSD-Insider algorithm reduces memory usage by up to 90% and execution time by up to 77% compared to the SSD-Insider algorithm and achieves the same detection accuracy. In addition, the AdvanSSD-Insider algorithm can monitor 10 times longer than the SSD-Insider algorithm in same memory condition. As a result, detection accuracy is increased for some ransomware which was difficult to detect using previous algorithm.

• Biomolecules & Therapeutics
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• v.27 no.1
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• pp.71-77
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• 2019

Previous studies have shown that spinosin was implicated in the modulation of sedation and hypnosis, while its effects on learning and memory deficits were rarely reported. The aim of this study is to investigate the effects of spinosin on the improvement of cognitive impairment in model mice with Alzheimer's disease (AD) induced by $A{\beta}_{1-42}$ and determine the underlying mechanism. Spontaneous locomotion assessment and Morris water maze test were performed to investigate the impact of spinosin on behavioral activities, and the pathological changes were assayed by biochemical analyses and histological assay. After 7 days of intracerebroventricular (ICV) administration of spinosin ($100{\mu}g/kg/day$), the cognitive impairment of mice induced by $A{\beta}_{1-42}$ was significantly attenuated. Moreover, spinosin treatment effectively decreased the level of malondialdehyde (MDA) and $A{\beta}_{1-42}$ accumulation in hippocampus. $A{\beta}_{1-42}$ induced alterations in the expression of brain derived neurotrophic factor (BDNF) and B-cell lymphoma-2 (Bcl-2), as well as inflammatory response in brain were also reversed by spinosin treatment. These results indicated that the ameliorating effect of spinosin on cognitive impairment might be mediated through the regulation of oxidative stress, inflammatory process, apoptotic program and neurotrophic factor expression,suggesting that spinosin might be beneficial to treat learning and memory deficits in patients with AD via multi-targets.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.1-8
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• 2022

In this paper, we design and implement a GPU-based parallel algorithm to effectively solve the traveling salesman problem through an ant color system. The repetition process of generating hundreds or thousands of tours simultaneously in TSP utilizes GPU's task-level parallelism, and the update process of pheromone trails data actively exploits data parallelism by 32x32 thread blocks. In particular, through simultaneous memory access of multiple threads, the coalesced accesses on continuous memory addresses and concurrent accesses on shared memory are supported. This experiment used 127 to 1002 city data provided by TSPLIB, and compared the performance of sequential and parallel algorithms by using Intel Core i9-9900K CPU and Nvidia Titan RTX system. Performance improvement by GPU parallelization shows speedup of about 10.13 to 11.37 times.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.12
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• pp.419-428
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• 2022

Since in-place updates for pages are not allowed in flash memory, all new page writes should be written in an out-of-place manner. The old overwritten pages are invalidated. Such invalidated pages eventually trigger the costly garbage collection process. Since the garbage collection causes numerous read and write operations, it is one of the flash memory's major performance issues. In 2R, it modified the garbage collection algorithm, which applies the I/O characteristics of the On-Line Transaction Process workload to improve the Write Amplification Factor. However, this algorithm has a region pollution problem. Therefore, in this paper, we developed 2R++ that additionally separates pages with long access intervals to solve the region pollution problem. 2R++ introduces an extra bit per block to separate warm pages based on a second chance mechanism. Prevents warm pages from being misidentified as cold pages to solve region pollution problem. We conducted the experiments on TPC-C and Linkbench to make the performance comparison. The experiment showed that 2R++ achieved a Write Amplification Factor improvement of 57.8% and 13.8% compared to 2R, respectively.