• Animal cells and systems
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• v.13 no.3
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• pp.267-274
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• 2009

The dissociative culture technique of Aplysia neuron is one of the key methods that have been used for studies of cellular and molecular mechanisms of neuronal functioning. However, despite the advantages this method offers as an experimental model, its technical efficiency has had room for improvement. In this study, we examined certain putative factors that might affect the culture quality. The effects of neuronal damage induced by physical injuries, heat shock, and surface protein degradation were evaluated along with the correlation between the culture quality and animal behavior. As a result, we found that physical injury can be a critical factor that affects culture quality, whereas the heat shock and surface protein degradation had negligible effect on it. In addition, we discovered that siphon retraction time was not a good measurement for healthy neurons. Based on these findings, we suggest here an improved method in which the degree of physical injury is reduced by means of multiple protease treatment.

• ETRI Journal
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• v.36 no.5
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.4
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• pp.205-210
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• 2014

Cache based live migration method utilizes a cache, which is accessible to both side (remote and local), to reduce the virtual machine migration time, by transferring only irredundant data. However, address space layout randomization (ASLR) is proved to reduce the memory duplicate ratio between targeted migration memory and the migration cache. In this pager, we analyzed the behavior of ASLR to find out how it changes the physical memory contents of virtual machines. We found that among six virtual memory regions, only the modification to stack influences the page-level memory duplicate ratio. Experiments showed that: (1) the ASLR does not shift the heap region in sub-page level; (2) the stack reduces the duplicate page size among VMs which performed input replay around 40MB, when ASLR was enabled; (3) the size of memory pages, which can be reconstructed from the fresh booted up state, also reduces by about 60MB by ASLR. With those observations, when applying cache-based migration method, we can omit the stack region. While for other five regions, even a coarse page-level redundancy data detecting method can figure out most of the duplicate memory contents.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.3
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• pp.13-19
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• 2016

Spark, an in-memory big-data processing framework is popular to use for real-time processing workload. Spark can store all intermediate data in the cluster memory so that Spark can minimize I/O access. However, when the resident memory of workload is larger that the physical memory amount of the cluster, the total performance can drop dramatically. In this paper, we analyse the factors of bottleneck on PageRank Application that needs many memory through experiment, and cluster the Spark with Tachyon File System for using memory to solve the factor of bottleneck and then we improve the performance about 18%.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.4
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• pp.91-103
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• 2021

Purpose : This study aimed to evaluate the effects of a cognitive enhancement brain yoga program on short-term memory and serum brain-derived neurotrophic factor (BDNF) levels according to the cognitive state in men aged 20-29 years. Methods : Thirty healthy volunteers aged 20-29 years were divided into four groups: brain yoga group, yoga group, combined exercise group, and control group. Seven people were assigned randomly per group. A single-session intervention was conducted over 50 min and consisted of three parts: warm-up, main exercise (brain yoga, yoga, combined exercise, or non-exercise), and cool-down. Serum BDNF levels were measured using enzyme-linked immunosorbent assay, and short-term memory was evaluated using the forward number span test before and after the intervention. Results : BDNF levels significantly increased within the brain yoga group after the intervention (from 28874.37±5185.57 to 34074.80±7321.12, p=.003), whereas there were no significant differences pre-and post-intervention in the other groups. The inter-group comparison showed a significant interaction between the brain yoga group and the combined exercise group (p=.036) but no significant interaction between any of the other groups. Forward number span scores were significantly increased in the brain yoga group (from 9.43±9.83 to 23±7.92, p=.012) and theyoga group after the intervention (from 13.43±9.41 to 24.14±8.45, p=.011), whereas there were no significant changes after the intervention in any other groups. Conclusion : Our findings showed that a single-session, 50-minute brain yoga exercise improved short-term memory and increased serum BDNF levels in healthy men aged 20-29 years and that yoga improved only short-term memory in healthy men of this age group.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.81-86
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• 2023

SSD (solid state disk), which is flash memory-based storage device, has the advantages of high density and fast data processing. Therefore, it is being utilized as a storage device for high-capacity data storage systems that manage rapidly increasing big data. However, flash memory, a storage media, has a physical limitation that when the write/erase operation is repeated more than a certain number of times, the cells are worn out and can no longer be used. In this paper, we propose a method for converting defective multi-bit cells into single-bit cells to reduce the defect rate of flash memory and extend its lifetime. The proposed idea distinguishes the defects and treatment methods of multi-bit cells and single-bit cells, which have different physical characteristics but are treated as the same defect, and converts the expected defective multi-bit cells into single-bit cells to improve the defect rate and extend the overall lifetime. Finally, we demonstrate the effectiveness of our proposed idea by measuring the increased lifetime of SSD through simulations.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.1
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• pp.1-13
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• 2009

Flash memory is widely used as a storage medium of mobile devices such as MP3 players, cellular phones and digital cameras due to its tiny size, low power consumption and shock resistant characteristics. Currently, there are many studies to replace HDD with flash memory because of its numerous strong points. To use flash memory as a storage medium, FTL(Flash Translation Layer) is required since flash memory has erase-before-write constraints and sizes of read/write unit and erase unit are different from each other. Recently, new type of flash memory called "large block flash memory" is introduced. The large block flash memory has different physical structure and characteristics from previous flash memory. So existing FTLs are not efficiently operated on large block flash memory. In this paper, we propose an efficient FTL for large block flash memory based on FAST(Fully Associative Sector Translation) scheme and page-level mapping on data blocks.

• Electrical & Electronic Materials
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• v.8 no.6
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• pp.727-736
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• 1995

This paper examines the characteristics and physical properties of the scaled MONOS nonvolatile memory device for low programming voltage EEPROM. The capacitor-type MONOS memory devices with the nitride thicknesses ranging from 41.angs. to 600.angs. have been fabricated. As a result, the 5V-programmable MONOS device has been obtained with a 20ms programming time by scaling the nitride thickness to 57.angs. with a tunneling oxide thickness of 19.angs. and a blocking oxide thickness of 20.angs.. Measurement results of the quasi-static C-V curves indicate, after 10$\^$6/ write/erase cycles, that the devices are degraded due to the increase of the silicon-tunneling oxide interface traps. The 10-year retention is impossible for the device with a nitride less than 129.angs.. However, the MONOS memory device with 10-year retentivity has been obtained by increasing the blocking oxide thickness to 47.angs.. Also, the memory traps such as the nitride bulk trap and the blocking oxide-nitride interface trap have been investigated by measuring the maximum flatband voltage shift and analyzing through the best fitting method.

• Korean Institute of Interior Design Journal
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• v.21 no.2
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• pp.23-34
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• 2012

After the modern age, the rapid urbanizationhad a big impact on the then architecture. R. Venturi and A. Rossi are two of the leading architects, developing architecture in cities in the US and Europe respectively. This study shed light on a tangible and intangible meaning and interpretation of urban landscapes through their architectural thoughts and architectures. The followings are the physical and intangible meaning and interpretation in architectural thoughts and works of those two architects. Venturi understood that iconological landscapes at the roadside in large citiesare the nature of physical landscapes. To Venturi, the façades of buildings at the roadside are a part of signage such as traffic lights and road signs, and those façades have the meaning of symbolic systems beyond simple physical landscapes. To A. Rossi, types of buildings as physical townscapes are a key role supporting raw data of classification in architecture. And also, those types have significance of the basic data shedding light on the principles and history of cities. For intangible factors in R. Venturi's architecture, daily routine, function and use, time, a use for a building and others form complex architecture. And also, those factors describe shared values of the same period as the façades of buildings and complex symbols and formative lexicons in metaphorical terms. For A. Rossi's intangible factors, 'collective memory' is buried in inhabitants of the city, and with that, the city is a place for memory to its inhabitants. What is more, cities' monuments have intangible landscapes like 'sustainability', 'permanence' and so on. With lots of events happening throughoutcities, those monuments are the whole images of cities giving the value to the urban buildings that reside in cities. Finally, R. Venturi's all-encompassing complex architecture concept was extended on a tangible and intangible point of townscapes. It was found that A. Rossi's tangible thought was formed from the whole landscape of historic cities in then Italy as the background of time and place. Also, With types of urban buildings and 'collective memory', A. Rossi drew architectural norms and formats of unchangeable types.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.