• ETRI Journal
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• 제28권3호
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• pp.320-328
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• 2006

Using biometrics to verify a person's identity has several advantages over the present practice of personal identification numbers (PINs) and passwords. To gain maximum security in a verification system using biometrics, the computation of the verification as well as the storing of the biometric pattern has to take place in a smart card. However, there is an open issue of integrating biometrics into a smart card because of its limited resources (processing power and memory space). In this paper, we propose a speaker verification algorithm using a support vector machine (SVM) with a very few features, and implemented it on a 32-bit smart card. The proposed algorithm can reduce the required memory space by a factor of more than 100 and can be executed in real-time. Also, we propose a hardware design for the algorithm on a field-programmable gate array (FPGA)-based platform. Based on the experimental results, our SVM solution can provide superior performance over typical speaker verification solutions. Furthermore, our FPGA-based solution can achieve a speed-up of 50 times over a software-based solution.

• 한국재료학회지
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• 제12권9호
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• pp.718-723
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• 2002

$Ti_{1-x}$ $Al_{ x}$N thin films as barrier layer for memory devices application were deposited by reactive magnetron sputtering. The crystallinity, micro-structure, oxidation resistance and oxidation mechanism of films were investigated as a function of Al content. Lattice parameter and grain size of thin films were decreased with increasing the Al content Oxidation of the film with higher Al content is slow and then, total oxide thickness is thinner than that of lower Al content film. Oxide layer formed on the surface is AlTiNO layer. Oxidation of $Ti_{1-x}$ /$Al_{x}$ N barrier layer is diffusion limited process and thickness of oxide layer with oxidation time increased with a parabolic law. The activation energy of oxygen diffusion, Ea and diffusion coefficient, D of $Ti_{0.74}$ /X$0.74_{0.26}$N film is 2.1eV and $10^{-16}$ ~$10^{-15}$ $\textrm{cm}^2$/s, respectively. $_Ti{1-x}$ /$Al_{x}$ XN barrier layer showed good oxidation resistance.

• 한국멀티미디어학회논문지
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• 제20권5호
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• pp.769-781
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• 2017

Deep learning networks like Convolutional Neural Networks (CNNs) show successful performances in many computer vision applications such as image classification, object detection, and so on. For implementation of deep learning networks in embedded system with limited processing power and memory, deep learning network may need to be simplified. However, simplified deep learning network cannot learn every possible scene. One realistic strategy for embedded deep learning network is to construct a simplified deep learning network model optimized for the scene images of the installation place. Then, automatic training will be necessitated for commercialization. In this paper, as an intermediate step toward automatic training under fisheye camera environments, we study more precise human localization in fisheye images, and propose an accurate human localization method, Automatic Ground-Truth Labelling Method (AGTLM). AGTLM first localizes candidate human object bounding boxes by utilizing GoogLeNet-LSTM approach, and after reassurance process by GoogLeNet-based CNN network, finally refines them more correctly and precisely(tightly) by applying saliency object detection technique. The performance improvement of the proposed human localization method, AGTLM with respect to accuracy and tightness is shown through several experiments.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.359-373
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• 2019

For clustering large-scale data, which cannot be loaded into memory entirely, incremental clustering algorithms are very popular. Usually, these algorithms only concern the within-cluster compactness and ignore the between-cluster separation. In this paper, we propose two incremental fuzzy compactness and separation (FCS) clustering algorithms, Single-Pass FCS (SPFCS) and Online FCS (OFCS), based on a fuzzy scatter matrix. Firstly, we introduce two incremental clustering methods called single-pass and online fuzzy C-means algorithms. Then, we combine these two methods separately with the weighted fuzzy C-means algorithm, so that they can be applied to the FCS algorithm. Afterwards, we optimize the within-cluster matrix and betweencluster matrix simultaneously to obtain the minimum within-cluster distance and maximum between-cluster distance. Finally, large-scale datasets can be well clustered within limited memory. We implemented experiments on some artificial datasets and real datasets separately. And experimental results show that, compared with SPFCM and OFCM, our SPFCS and OFCS are more robust to the value of fuzzy index m and noise.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.112-115
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• 2009

RDS(Radio Data System) 에서의 PI Code 검색 기법은 이동체(Vehicle)에서 원하는 방송을 지속적으로 자동 선국할 수 있는 유일한 방법이다. Original channel의 신호가 나빠지기 전에 좀더 낳은 신호를 찾기 위한, 또한 Weak signal Area에서 벗어나면서 원하는 방송을 빠르게 찾기 위한, 효율적이면서도 빠른 PI Code 검색 기법은 모든 RDS System에서 연구되고 있으나, Embedded system 특성상 Memory size의 제약 등으로 인해, 기 알려진 여러 방법을 쉽게 적용할 수 없는 상황이다. 본 논문은 Embedded System Environment를 십분 고려하여, 간략하면서도 효율적인 PI Code 검출에 대한 기법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1341-1368
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• 2024

The concept of privacy-preserving collaborative filtering (PPCF) has been gaining significant attention. Due to the fact that model-based recommendation methods with privacy are more efficient online, privacy-preserving memory-based scheme should be avoided in favor of model-based recommendation methods with privacy. Several studies in the current literature have examined ant colony clustering algorithms that are based on non-privacy collaborative filtering schemes. Nevertheless, the literature does not contain any studies that consider privacy in the context of ant colony clustering-based CF schema. This study employed the ant colony clustering model-based PPCF scheme. Attacks like shilling or profile injection could potentially be successful against privacy-preserving model-based collaborative filtering techniques. Afterwards, the scheme's robustness was assessed by conducting a shilling attack using six different attack models. We utilize masked data-based profile injection attacks against a privacy-preserving ant colony clustering-based prediction algorithm. Subsequently, we conduct extensive experiments utilizing authentic data to assess its robustness against profile injection attacks. In addition, we evaluate the resilience of the ant colony clustering model-based PPCF against shilling attacks by comparing it to established PPCF memory and model-based prediction techniques. The empirical findings indicate that push attack models exerted a substantial influence on the predictions, whereas nuke attack models demonstrated limited efficacy.

• Biomolecules & Therapeutics
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• 제32권3호
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• pp.309-318
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• 2024

Compared to other organs, the brain has limited antioxidant defenses. In particular, the hippocampus is the central region for learning and memory and is highly susceptible to oxidative stress. Glial cells are the most abundant cells in the brain, and sustained glial cell activation is critical to the neuroinflammation that aggravates neuropathology and neurotoxicity. Therefore, regulating glial cell activation is a promising neurotherapeutic treatment. Quinic acid (QA) and its derivatives possess anti-oxidant and anti-inflammatory properties. Although previous studies have evidenced QA's benefit on the brain, in vivo and in vitro analyses of its anti-oxidant and anti-inflammatory properties in glial cells have yet to be established. This study investigated QA's rescue effect in lipopolysaccharide (LPS)-induced behavior impairment. Orally administering QA restored social impairment and LPS-induced spatial and fear memory. In addition, QA inhibited proinflammatory mediator, oxidative stress marker, and mitogen-activated protein kinase (MAPK) activation in the LPS-injected hippocampus. QA inhibited nitrite release and extracellular signal-regulated kinase (ERK) phosphorylation in LPS-stimulated astrocytes. Collectively, QA restored impaired neuroinflammation-induced behavior by regulating proinflammatory mediator and ERK activation in astrocytes, demonstrating its potential as a therapeutic agent for neuroinflammation-induced brain disease treatments.

• 한국정보과학회논문지:데이타베이스
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• 제36권3호
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• pp.235-246
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• 2009

기존 서버에서 담당하던 접근제어를 서버에 비해 제약을 갖는 클라이언트에서 처리하고자 하는 요구가 생겨남에 따라 자원 제약을 갖는 환경에서 효율적이고 안전하게 실의를 처리할 수 있는 방법이 필요하게 되었다. 기존의 접근제어 연구는 안전성에 초점을 맞추어 왔기 때문에 효율성 측면에 대한 고려가 적었으며, 최근 스트림 환경에서 보안 문제가 대두되면서 접근제어를 포함한 보안 측면의 연구가 시작되었다. 본 논문은 XML 데이터 스트립을 PDA나 휴대용 단말기와 같은 자원의 제약이 있는 클라이언트에서 안전하고 효율적으로 다루기 위한 방법을 제안한다. 본 연구는 유효한 XML 스트림 환경에서 첫째로 한정된 메모리 내에서 안전한 결과를 내기 위해 오버 헤드가 매우 적은 접근제어 처리 방법을 제안하고 있으며, 둘째로 접근제어 추가로 인한 오버헤드를 상쇄시키기 위해 처리 단계 마다 최적화가 가능한 부분들을 찾아 성능을 개선하는 방법을 제안한다. 실험을 통해 제안하는 방법의 우수성을 분석한다.

• 정보처리학회논문지D
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• 제16D권1호
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• pp.27-42
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• 2009

유비쿼터스 컴퓨팅의 실현을 위해서는 이동 디바이스 등 클라이언트의 제약된 자원을 효율적으로 사용하는 기법이 요구된다. 메모리 용량이 크지 않은 이동 디바이스의 경우, 대용량 XML 데이터에 대한 질의 처리를 수행하기 위해서는 XML 스트림 질의 처리 기술의 활용이 필수적이다. 최근에 서버에서 XML 문서를 XML 조각(XML fragment)으로 분할하여 스트리밍하고 클라이언트에서 이 조각 스트림을 받아 질의를 처리하는 기법들이 제안되었다. XML 조각 스트림 질의 처리에 있어 XML 문서가 분할되는 방법에 따라 자원 사용(질의 처리 시간 및 메모리 사용량) 면에서 큰 차이가 날 수 있기 때문에 효율적인 XML 문서 분할 방법이 요구된다. 본 논문에서는 클라이언트의 질의 처리 시 자원 사용 효율을 높이기 위한 XML 문서 분할 기법을 제시한다. 이를 위하여 먼저 XML 조각 스트림 질의 처리의 비용 모델을 제시하고, 자원 효율적인 XML 문서 분할 알고리즘을 제시한다. 구현 및 성능 평가 결과 본 논문에서 제시한 기법이 기존 기법들에 비해 질의 처리 시간 및 메모리 사용량 양면 모두에서 우수한 것으로 나타났다. 본 논문의 기여는 XML 조각 스트림 질의 처리 기술의 실용화 가능성을 기존 기술에 비해 한 층더 높였다는 데 있다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2016년도 제50회 동계 정기학술대회 초록집
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• pp.285-285
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• 2016

Resistive random access memory devices have been widely studied due to their high performance characteristics, such as high scalability, fast switching, and low power consumption. However, fluctuation in operational parameters remains a critical weakness that leads to device failures. Although the random formation and rupture of conducting filaments (CFs) in an oxide matrix during resistive switching processes have been proposed as the origin of such fluctuations, direct observations of the formation and rupture of CFs at the device scale during resistive switching processes have been limited by the lack of real-time large-area imaging methods. Here, a novel imaging method is proposed for monitoring CF formation and rupture across the whole area of a memory cell during resistive switching. A hybrid structure consisting of a resistive random access memory and a light-emitting diode enables real-time monitoring of CF configuration during various resistive switching processes including forming, semi-forming, stable/unstable set/reset switching, and repetitive set switching over 50 cycles.