• Animal cells and systems
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• v.12 no.4
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• pp.203-209
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• 2008

Berberine, an isoquinoline alkaloid found in Coptidis Rhizoma(goldenthread) extract, has multiple pharmacological effects such as anti-inflammatory, antimicrobial and anti-ischemic effects. In the present study, we examined the effects of berberine on neuronal survival and differentiation in a hippocampal precursor cell line and in the memory deficient rat model. Berberine increased in a dose dependent manner the survival of hippocampal precursor cells as well as differentiated cells. In addition, berberine promoted neuronal differentiation of hippocampal precursor cells. In the memory deficient rat model induced by stereotaxic injection of ibotenic acid into entorhinal cortex(Ibo model), hippocampal cells were increased about 2.7 fold in the pyramidal layer of CA1 region and about 2 fold in the dentate gyrus by administration of berberine after 2 weeks of ibotenic acid injection. Furthermore, neuronal cells immunoreactive to calbindin were increased in the hippocampus and entorhinal cortex area by administration of berberine. Taken together, these results suggest that berberine has neuroprotective effect in the Ibo model rat brain by promoting the neuronal survival and differentiation.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.377-382
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• 2010

With the advent of flash memory based new storage device (SSD), there is considerable interest within the computer industry in using flash memory based storage devices for many different types of application. The dynamic index structure of large text collections has been a primary issue in the Information Retrieval Applications among them. Previous studies have proven the three approaches to be effective: In- Place, merge-based index structure and a combination of both. The above-mentioned strategies have been researched with the traditional storage device (HDD) which has a constraint on how keep the contiguity of dynamic data. However, in case of the new storage device, we don' have any constraint contiguity problems due to its low access latency time. But, although the new storage device has superiority such as low access latency and improved I/O throughput speeds, it is still not well suited for traditional dynamic index structures because of the poor random write throughput in practical systems. Therefore, using the experimental performance evaluation of various index maintenance schemes on the new storage device, we propose an efficient index structure for new storage device that improves significantly the index maintenance speed without degradation of query performance.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1120-1127
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• 2009

The commensurate number of the attacks and infringement targeting a vulnerability of the game service has been increasing constantly, due to the dramatic growth and expansion of the impact of the game industry. However, there exist no subsequent researches for the differentiated technology, which is to prevent the reverse function of the game service. Therefore, in this study, we examined the current status of infringement toward online game services which are provided in the market currently and designed the proper technical measures for a manipulation of the game service which is the most vulnerable part. We have encrypted an execution file and decrypted it in real time process. Furthermore, we conducted debugging, disassemble, and prevented a its own memory dump, also concealed the information to overcome the module dependency to preclude a manipulation.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.559-566
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• 2005

ALTIBASE is the relational main memory DBMS that enables us to develop the high performance and fault tolerant applications. It guarantees the short and predictable execution time as well as the basic functionality of conventional disk-based DBMS. We present the overview of system architecture and the performance analysis with respect to the various design choices. The assorted experiments are performed under the various environments. The results of TPC-H and Wisconsin benchmark tests are described. We illustrate the various performance comparisons under the various index mechanisms, the replication models, the transaction durabilities, and the application structures. A performance study shows the ALTIBASE system can be applied to the wide area of industrial DBMS fields.

• Journal of IKEEE
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• v.27 no.3
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• pp.296-302
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• 2023

As Multimedia industry has evolved, it has become possible to display resolutions in various formats. Therefore, the performance of a scaler algorithm that converts resolutions while maintaining high quality and its hardware implementation are important. Considering the hardware design of an image up/down scaler, this paper proposes a combinatorial scaler algorithm that uses modified bilinear interpolation in the vertical direction and bicubic interpolation in the horizontal direction to reduce the line memory burden. Through quantitative and qualitative evaluations, this paper compared the performance of the proposed algorithm with three other well-known algorithms, and also compared the hardware burden of its hardware implementation. This paper used a sinusoidal signal and eight typical images for performance evaluation.

• The Journal of Bigdata
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• v.7 no.2
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• pp.217-224
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• 2022

Since online shopping has become common, people can easily buy fashion goods anytime, anywhere. Therefore, consumers quickly respond to various environmental variables such as weather and sales prices. Therefore, utilizing big data for efficient inventory management has become very important in the fashion industry. In this paper, the changes in sales volume of fashion goods due to changes in temperature is analyzed via the proposed big data analysis algorithm by utilizing actual big data from Korean fashion company 'A'. According to the simulation results, it was confirmed that Bidirectional-LSTM(Bi-LSTM) compared to LSTM(Long Short-Term Memory) takes more simulation time about more than 50%, but the prediction accuracy of non-periodic time series data such as clothing product sales data is the same.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.191-204
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• 2013

In this paper, we investigated the correlation outputs of Daejeon correlator at the viewpoints of the buffer memory setting related to the fine delay tracking and the under/overflow issue in FFT modules, in order to eliminate DC-like component and phase concentration to 0 degree. As the ring buffer memory is being used for the fine delay tracking, the DC-like component in correlation outputs is generated by improper setting of data read/write address, and then that address setting method is modified to exclude a polluted FFT segment in correlation processing when crossing the port/stream boundary. The phase concentration to 0 degree at beginning of bandpass is caused by inadequate scaling factors, which may be the origins of under/overflow occurred at internal computation of FFT stage. With the revised method of the ring buffer memory setting and the scaling factors in FFT, we could obtain higher signal-to-noise ratio and flux density, compared to the previous method, through the correlation processing of true observational data.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.447-453
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• 2021

The whole world was confused, unintended "COVID-19". It has become a constant phenomenon, not a temporary one, and people are getting used to this era. Among them, We are combating the form of "the film" which is playing a role of a multiplex in Korean film industry. Now we have studied the development of the future korean industry based on the movie theater form through our cultural industry, New platform OTT. As a result for the research, the OTT platform, which is located in one genre today, should be regarded as an opportunity to develop films, and the movie theater, which is a part of the development of the film industry, differs from the OTT platform. with "memory of space", the result was that "The audience's footsteps can move again." The crisis of "COVID-19" should bring about the consequences of turning into opportunity.

• Journal of Global Scholars of Marketing Science
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• v.16 no.2
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• pp.109-132
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• 2006

A Major aim of this study is to test the hypothesis that there is an association between empowerment, organizational memory, and new product creativity. In addition to exploring these relationships, this study examines the effect of new product creativity on new product performance, and identify the moderating effects of market uncertainty in the relationships between new product creativity and performance. For this purposes, we developed a research model based on the literature reviews of empowerment, organizational memory, market uncertainty, and new product creativity. A total of 121 usable survey responses has been used in the empirical research for foods manufacturing industry. The findings indicate that (1) Empowerment has a positive effect on new product creativity, (2) Organizational memory has a positive effect on new product creativity, (3) New product novelty has a positive effect on new product performance, and (4) Only competition uncertainty has a moderating effects between the new product meaningfulness and performance. The findings have implications for managers wishing to acquire the new product creativity and to better the new product development performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.847-857
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• 2018

As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.