• 제목/요약/키워드: attention mechanism

검색결과 780건 처리시간 0.029초

Suppressing NF-κB/Caspase-1 Activation is a Mechanism Involved in the Anti-inflammatory Effect of Rubi Fructus in Stimulated HMC-1 Cells

  • Mi-Ok Yang;Noh-Yil Myung
    • 대한의생명과학회지
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    • 제29권3호
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    • pp.137-143
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    • 2023
  • Inflammation plays an important role in immune system's response to tissue injury and biological stimuli. However, excessive inflammation can cause tissue damage. Therefore, the development of naturally derived anti-inflammatory agents have received broad attention. In this study, we investigated the anti-inflammatory mechanism of Rubi Fructus (RF) extract on the mast cell-mediated inflammatory response. To determine the regulatory mechanism of RF in inflammatory reaction, we evaluated the effects of RF on secretion of interleukin (IL)-8, IL-6 and tumor necrosis factor (TNF)-α and activation of nuclear factor-κB (NF-κB) and caspase-1 in activated human mast cells-1 (HMC-1). The results showed that RF attenuated IL-8, IL-6 and TNF-α secretion in a concentration-dependent manner. Moreover, RF significantly attenuated caspase-1and NF-κB activation in activated HMC-1. Conclusively, the present results provide evidence that RF may be a promising agent for anti-inflammatory therapy.

Scalable Blockchain Storage Model Based on DHT and IPFS

  • Chen, Lu;Zhang, Xin;Sun, Zhixin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권7호
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    • pp.2286-2304
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    • 2022
  • Blockchain is a distributed ledger that combines technologies such as cryptography, consensus mechanism, peer-to-peer transmission, and time stamping. The rapid development of blockchain has attracted attention from all walks of life, but storage scalability issues have hindered the application of blockchain. In this paper, a scalable blockchain storage model based on Distributed Hash Table (DHT) and the InterPlanetary File System (IPFS) was proposed. This paper introduces the current research status of the scalable blockchain storage model, as well as the basic principles of DHT and the InterPlanetary File System. The model construction and workflow are explained in detail. At the same time, the DHT network construction mechanism, block heat identification mechanism, new node initialization mechanism, and block data read and write mechanism in the model are described in detail. Experimental results show that this model can reduce the storage burden of nodes, and at the same time, the blockchain network can accommodate more local blocks under the same block height.

딥 러닝 기반 휴먼 모션 디노이징 (Deep Learning-Based Human Motion Denoising)

  • 김성욱;임현승;김종민
    • 전기전자학회논문지
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    • 제23권4호
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    • pp.1295-1301
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    • 2019
  • 본 논문에서는 어텐션 기법을 적용한 양방향 순환신경망을 이용하여 새로운 휴먼 모션 디노이징 방법을 제안한다. 본 방법을 이용하면, 단일 3D 깊이 센서 카메라에서 캡처된 노이즈가 포함된 사람의 움직임이 잘 교정된 자연스러운 움직임으로 자동 조정된다. 양방향 순환신경망에 어텐션 기법을 도입하면, 입력으로 들어온 움직임을 인코딩할 때 여러 자세 중에 더 중요한 자세가 있는 프레임에 더 높은 어텐션 가중치를 부여함으로써, 다른 딥 러닝 네트워크와 비교해 더 나은 최적화 결과와 더 높은 정확도를 보인다. 실험을 통해 본 논문에서 제시한 방법이 다양한 스타일의 움직임과 노이즈를 효과적으로 처리함을 확인하였으며, 제시한 방법은 모션 캡처 후처리 단계의 애플리케이션으로 충분히 사용 가능할 것으로 기대된다.

어텐션 기반 게이트 순환 유닛을 이용한 수동소나 신호분류 (Passive sonar signal classification using attention based gated recurrent unit)

  • 이기배;고건혁;이종현
    • 한국음향학회지
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    • 제42권4호
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    • pp.345-356
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    • 2023
  • 수동소나의 표적신호는 수초 내 세기의 변화를 갖는 협대역 고조파 특성과 로이드 거울 효과에 의한 장시간 주파수 변이 특성을 나타낸다. 본 논문에서는 지역 및 전역적 시계열 특징을 학습하는 게이트 순환 유닛 기반의 신호분류 알고리즘을 제안한다. 제안하는 알고리즘은 게이트 순환 유닛을 이용한 다층 네트워크를 구성하고 확장된 연결을 통해 지역 및 전역적 시계열 특징들을 추출한다. 이후 어텐션 메커니즘을 학습하여 시계열 특징들을 가중하고 수동소나 신호를 분류한다. 공개된 수중 음향 데이터를 이용한 실험에서 제안된 네트워크는 96.50 %의 우수한 분류 정확도를 보였다. 이러한 결과는 기존의 잔차 연결된 게이트 순환 유닛 네트워크과 비교하여 4.17 % 높은 분류 정확도를 갖는다.

Enhancing Alzheimer's Disease Classification using 3D Convolutional Neural Network and Multilayer Perceptron Model with Attention Network

  • Enoch A. Frimpong;Zhiguang Qin;Regina E. Turkson;Bernard M. Cobbinah;Edward Y. Baagyere;Edwin K. Tenagyei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권11호
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    • pp.2924-2944
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    • 2023
  • Alzheimer's disease (AD) is a neurological condition that is recognized as one of the primary causes of memory loss. AD currently has no cure. Therefore, the need to develop an efficient model with high precision for timely detection of the disease is very essential. When AD is detected early, treatment would be most likely successful. The most often utilized indicators for AD identification are the Mini-mental state examination (MMSE), and the clinical dementia. However, the use of these indicators as ground truth marking could be imprecise for AD detection. Researchers have proposed several computer-aided frameworks and lately, the supervised model is mostly used. In this study, we propose a novel 3D Convolutional Neural Network Multilayer Perceptron (3D CNN-MLP) based model for AD classification. The model uses Attention Mechanism to automatically extract relevant features from Magnetic Resonance Images (MRI) to generate probability maps which serves as input for the MLP classifier. Three MRI scan categories were considered, thus AD dementia patients, Mild Cognitive Impairment patients (MCI), and Normal Control (NC) or healthy patients. The performance of the model is assessed by comparing basic CNN, VGG16, DenseNet models, and other state of the art works. The models were adjusted to fit the 3D images before the comparison was done. Our model exhibited excellent classification performance, with an accuracy of 91.27% for AD and NC, 80.85% for MCI and NC, and 87.34% for AD and MCI.

충전 특성과 어텐션 기반 LSTM을 활용한 개선된 리튬이온 배터리 SOH 예측 모델 (Improved SOH Prediction Model for Lithium-ion Battery Using Charging Characteristics and Attention-Based LSTM)

  • 류한일;이상훈;최덕재;박혁로
    • 스마트미디어저널
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    • 제12권11호
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    • pp.103-112
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    • 2023
  • 최근 리튬이온 배터리 사용이 늘어남에 따라 배터리 화재 및 사고 예방의 필요성이 대두되고 있다. 사고 예방을 위해서는 배터리 SOH(State of Health)를 예측하여 열화가 많이 진행된 배터리의 교체 시기를 확인하는 것이 필요하다. 본 논문에서는 배터리의 충전 과정에서 얻을 수 있는 최대 전압 도달 시간, 전류 변화 시간, 최대 온도 도달 시간, IC(Incremental Capacity) 등 4가지 배터리 열화 특성과 어텐션 메커니즘을 이용한 장단기 메모리(Long Short Term Memory, LSTM)를 사용하여 배터리의 열화 상태를 예측하는 모델을 제안한다. NASA에서 제공하는 배터리 데이터 세트를 사용해 제안하는 모델의 성능을 측정한 결과 일반적인 LSTM 모델을 사용하는 경우보다 예측성능의 개선을 확인할 수 있었고, 특히 배터리 교체 주기에 가까운 SOH 90-70% 구간에서 더 우수한 성능을 보였다.

특징 맵 중요도 기반 어텐션을 적용한 복소 스펙트럼 기반 음성 향상에 관한 연구 (A study on speech enhancement using complex-valued spectrum employing Feature map Dependent attention gate)

  • 정재희;김우일
    • 한국음향학회지
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    • 제42권6호
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    • pp.544-551
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    • 2023
  • 잡음 음성의 지각적 품질과 명료도 향상을 위해 활용되는 음성 향상은 크기 스펙트럼을 이용한 방법에서 크기와 위상을 같이 향상시킬 수 있는 복소 스펙트럼을 이용한 방법으로 연구되어왔다. 본 논문에서는 잡음 음성의 명료도와 품질을 더욱 향상시키기 위해 복소 스펙트럼 기반 음성 향상 시스템에 어텐션 기법을 적용하는 방안에 관해 연구를 수행하였다. 어텐션 기법은 additive attention을 기반으로 수행하며 복소 스펙트럼의 특성을 고려하여 어텐션 가중치를 계산할 수 있도록 하였다. 또한 특징 맵의 중요도를 고려하기 위해 전역 평균 풀링 연산을 같이 사용하였다. 복소 스펙트럼 기반 음성 향상은 Deep Complex U-Net(DCUNET) 모델을 기반으로 수행하였으며, additive attention은 Attention U-Net 모델에서 제안된 방법을 기반으로 연구를 수행하였다. 거실 환경의 잡음 데이터에 대해 음성 향상을 수행한 결과, 제안한 방법이 Source to Distortion Ratio(SDR), Perceptual Evaluation of Speech Quality(PESQ), Short Time Objective Intelligibility(STOI) 평가 지표에서 기준 모델보다 개선된 성능을 보였으며, 낮은 Signal-to-Noise Ratio(SNR) 조건의 다양한 배경 잡음 환경에 대해서도 일관된 성능 향상을 보였다. 이를 통해 제안한 음성 향상 시스템이 효과적으로 잡음 음성의 명료도와 품질을 향상시킬 수 있음을 보여주었다.

Multi-objective Genetic Algorithm 을 이용한 얀센 메커니즘의 목표 궤적 트래킹 기반 최적 설계 (Optimized design of Jansen mechanism based on target trajectory tracking method using multi-objective genetic algorithm)

  • 허준;허영건
    • EDISON SW 활용 경진대회 논문집
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    • 제5회(2016년)
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    • pp.455-462
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    • 2016
  • Recently, followed by rapid growth of robotics field, multi-linkage mechanism which can even pass by rough road is getting lots of attention. In this paper, I focused on Jansen mechanism. It's a kinematics object which is named after Dutch artist Theo jansen. Jansen mechanism embraces structure and mechanism which creates locomotion with the combination of the power and simple structure. Theo jansen suggests a 'Holy number'. It's an ideal ratio of leg components length. However, if there's desired gait locomotion, you have to adjust the ratio and the length. But even slight change of the length could cause a big change at the end-point. To solve this problem, I suggest a reverse engineering method to get a ratio of each links by nonlinear optimization with pre-set desired trajectory. First, we converted a movement of the joint of Jansen mechanism to vectors by kinematics analysis of multi-linkage structure. And we showed the trajectory at the end-point. After that, we set desired trajectory which we found most ideal. Then we got the length of the leg components which draws a trajectory as same as trajectory we set, using Multi-objective genetic algorithm toolbox in MATLAB. Result is verified by Edison designer and mSketch. And we analyzed if it could pass through the obstruction which is set dynamically.

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A Fast and Scalable Inter-Domain MPLS Protection Mechanism

  • Huang, Chang-Cheng;Messier, Donald
    • Journal of Communications and Networks
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    • 제6권1호
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    • pp.60-67
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    • 2004
  • With the fast growth of Internet and a new widespread interest in optical networks, the unparalleled potential of Multi-Protocol Label Switching (MPLS) is leading to further research and development efforts. One of those areas of research is Path Protection Mechanism. It is widely accepted that layer three protection and recovery mechanisms are too slow for today’s reliability requirements. Failure recovery latencies ranging from several seconds to minutes, for layer three routing protocols, have been widely reported. For this reason, a recovery mechanism at the MPLS layer capable of recovering from failed paths in 10’s of milliseconds has been sought. In light of this, several MPLS based protection mechanisms have been proposed, such as end-to-end path protection and local repair mechanism. Those mechanisms are designed for intra-domain recoveries and little or no attention has been given to the case of non-homogenous independent inter-domains. This paper presents a novel solution for the setup and maintenance of independent protection mechanisms within individual domains and merged at the domain boundaries. This innovative solution offers significant advantages including fast recovery across multiple nonhomogeneous domains and high scalability. Detailed setup and operation procedures are described. Finally, simulation results using OPNET are presented showing recovery times of a few milliseconds.

TCP Delayed Window Update Mechanism for Fighting the Bufferbloat

  • Wang, Min;Yuan, Lingyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권10호
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    • pp.4977-4996
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    • 2016
  • The existence of excessively large and too filled network buffers, known as bufferbloat, has recently gained attention as a major performance problem for delay-sensitive applications. Researchers have made three types of suggestions to solve the bufferbloat problem. One is End to End (E2E) congestion control, second is deployment of Active Queue Management (AQM) techniques and third is the combination of above two. However, these solutions either seem impractical or could not obtain good bandwidth utilization. In this paper, we propose a Transmission Control Protocol(TCP)delayed window update mechanism which uses a congestion detection approach to predict the congestion level of networks. When detecting the network congestion is coming, a delayed window update control strategy is adopted to maintain good protocol performance. If the network is non-congested, the mechanism stops work and congestion window is updated based on the original protocol. The simulation experiments are conducted on both high bandwidth and long delay scenario and low bandwidth and short delay scenario. Experiment results show that TCP delayed window update mechanism can effectively improve the performance of the original protocol, decreasing packet losses and queuing delay while guaranteeing transmission efficiency of the whole network. In addition, it can perform good fairness and TCP friendliness.