• Proceedings of the KIEE Conference
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• 2006.07c
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• pp.1448-1449
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• 2006

Pb(Zr,Ti)$O_3$ is one of the most attractive ferroelectric materials for realizing the FeRAM due to its higher remanant polarization and the ability to withstand higher coercive fields. Generally, the ferroelectric materials were patterned by a plasma etching process for high-density FeRAM. The applicable possibility of CMP process to pattern Pb(Zr,Ti)$O_3$ instead of plasma etching process was investigated in our previous study for improvement of an angled sidewall which prevents the densification of ferroelectric memory and is apt to receive the plasma damage. Our previous study showed that good removal rate with the excellent surface roughness compared to plasma etching process were obtained by CMP process for the patterning of Pb(Zr,Ti)$O_3$. The suitable selectivity to TEOS without any damage to the structural property of Pb(Zr,Ti)$O_3$ was also guaranteed. In this study, the removal mechanism of $Pb_{1.1}(Zr_{0.52}Ti_{0.48})O_3$ coated by sol-gel method was investigated. Surface analysis of polished specimens at the best and worst conditions was carried out by XPS.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.1881-1883
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• 2005

In this study, PZT thin films were fabricated using sol-gel Processing onto $Si/SiO_2/Ti/Pt$ substrates. PZT sol with different Zr/Ti ratio(20/80, 30/70, 40/60, 52/48) were prepared, respectively. The films were fabricated by using the spin-coating method on substrates. The films were heat treated at $450^{\circ}C$, $650^{\circ}C$ by rapid thermal annealing(RTA). The preferred orientation of the PZT thin films were observed by X-ray diffraction(XRD), and Scanning electron microscopy(SEM). All of the resulting PZT thin films were crystallized with perovskite phase. The fine crystallinity of the films were fabricated. Also, we found that the ferroelectric properties from the dielectric constant of the PZT thin films were over 600 degrees, P-E hysteresis constant. And the leakage current densities of films were lower than $10^{-8}\;A/cm^2$. It is concluded that the PZT thin films by sol-gel process to be convinced of application for ferroelectric memory device.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.133-144
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• 2008

Clusters have become a popular alternative for building high-performance parallel computing systems. Today's high-performance system area network (SAN) protocols such as VIA and IBA significantly reduce user-to-user communication latency by implementing protocol stacks outside of operating system kernel. However, emerging parallel applications require a significant improvement in communication latency. Since the time required for transferring data between host memory and network interface (NI) make up a large portion of overall communication latency, the reduction of data transfer time is crucial for achieving low-latency communication. In this paper, Eager Data Transfer (EDT) mechanism is proposed to reduce the time for data transfers between the host and network interface. The EDT employs cache coherence interface hardware to directly transfer data between the host and NI. An EDT-based network interface was modeled and simulated on the Linux-based, complete system simulation environment, Linux/SimOS. Our simulation results show that the EDT approach significantly reduces the data transfer time compared to DMA-based approaches. The EDTbased NI attains 17% to 38% reduction in user-to-user message time compared to the cache-coherent DMA-based NIs for a range of message sizes (64 bytes${\sim}$4 Kbytes) in a SAN environment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07a
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• pp.9-12
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• 2004

In this paper, a new small sized Lateral Trench Electrode Power MOS was proposed. This new structure, called LTEMOS(Lateral Trench Electrode Power MOS), was based on the conventional lateral power MOS. But the entire electrodes of LTEMOS were placed in trench oxide. The forward blocking voltage of the proposed LTEMOS was improved by 1.5 times with that of the conventional lateral power MOS. The forward blocking voltage of LTEMOS was about 240 V. At the same size, an improvement of the forward blocking voltage of about 1.5 times relative to the conventional MOS was observed by using ISE-TCAD which was used for analyzing device's electrical characteristics. Because all of the electrodes of the proposed device were formed in each trench oxide, the electric field was crowded to trench oxide and punch-through breakdown was occurred, lately.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.171-171
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• 2007

Dysprosium-doped bismuth titanate (BDT) thin films were successfully deposited on Pt(111)/Ti/$SiO_2$/Si(100) substrates by liquid delivery MOCVD process and their structural and ferroelectric properties were characterized. Fabricated BDT thin films were found to be random orientations, which were confirmed by X-ray diffraction experiment and scanning electron microscope analysis. The crystallinity of the BDT films was improved and the average grain size increased as the crystallization temperature increased from 600 to $720^{\circ}C$ at an interval of $40^{\circ}C$. The BDT thin film annealed at $720^{\circ}C$ showed a large remanent polarization (2Pr) of $52.27\;{\mu}C/cm^2$ at an applied voltage of 5V. The BDT thin film exhibits a good fatigue resistance up to $1.0{\times}10^{11}$ switching cycles at a frequency of 1 MHz with applied pulse of ${\pm}5\;V$. These results indicate that the randomly oriented BDT thin film is a promising candidate among ferroelectric materials useti비 in lead-free nonvolatile ferroelectric random access memory applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.750-751
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• 2012

스마트폰의 급속한 확산과 함께 스마트폰 애플리케이션 시장이 빠르게 성장하고 있다. 이러한 성장세에 따라 많은 애플리케이션 개발자들이 생겨났으며, 다양한 콘텐츠와 수많은 애플리케이션이 개발되어지고 있다. 여기서 우리는 모바일 기기들의 제한적인 요소를 간과해서는 안 된다. 제한적인 모바일기기에서 유저가 만족할 만할 애플리케이션을 개발하기 위해서는 효율적인 자원 활용과 함께 효율적인 프로그래밍을 해야 할 필요가 있다. 본 논문은 안드로이드 NDK 및 SDK를 기반으로 Native C와 Java를 이용해 애플리케이션을 설계하고, 각 애플리케이션간의 알고리즘 수행속도, 프로세서 점유율측면에서 성능측정 실험을 수행했다. 실험 결과를 통해 보다 우수한 성능의 안드로이드 애플리케이션 개발 방법에 관해 연구했다. 성능측정 항목으로는 JNI delay, Integer, Floating point, Memory access algorithm, String이며, 실험은 삼성 갤럭시 S1에서 수행하였다.

• Journal of Ginseng Research
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• v.45 no.5
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• pp.599-609
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• 2021

Ginseng has long been considered as an herbal medicine. Recent data suggest that ginseng has antiinflammatory properties and can improve learning- and memory-related function in the central nervous system (CNS) following the development of CNS neuroinflammatory diseases such as Alzheimer's disease, cerebral ischemia, and other neurological disorders. In this review, we discuss the role of ginseng in the neurovascular unit, which is composed of endothelial cells surrounded by astrocytes, pericytes, microglia, neural stem cells, oligodendrocytes, and neurons, especially their blood-brain barrier maintenance, anti-inflammatory effects and regenerative functions. In addition, cell-cell communication enhanced by ginseng may be attributed to regeneration via induction of neurogenesis and angiogenesis in CNS diseases. Thus, ginseng may have therapeutic potential to exert cognitive improvement in neuroinflammatory diseases such as stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, and Alzheimer's disease.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.129-138
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• 2018

As recent applications are requiring more CPUs for their performance, manycore systems have evolved. Since existing operating systems do not provide performance scalability in manycore systems, Azalea, a multi-kernel based system, has been developed for supporting performance scalability. Unikernel is a new operating system technology starting with the concept of a library OS. Applying unikernel to Azalea enables an improvement in performance. In this paper, we first analyze the current technology trends of unikernel, and then discuss the applications and effects of unikernel to Azalea. Azalea-unikernel was built in a single image consisting of libOS, runtime libraries, and an application, and executed with the desired number of cores and memory size in bare-metal. In particular, it supports source and binary compatibility such that existing linux binaries can be rebuilt and executed in Azalea-unikernel, and already built binaries can be run immediately without modification with a better performance. It not only achieves a performance enhancement, it is also a more secure OS for manycore systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.