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Localization of Myocardial Infarction from 12 Lead ECG Empowered with Novel Machine Learning 基于新型机器学习的12导联心电图心肌梗死定位
Mazen Megahed, U. Jain, Michael T. Leasure, Adam A. Butchy
There are multiple modalities used to diagnose abnormalities of the heart consisting of various invasive and noninvasive tests. Patients may undergo multiple tests, progressing to more invasive methods at the expense of patient risk and cost to the pair. HEARTio, through machine learning and algorithmic processing our proprietary software, hopes to improve the accuracy of the electrocardiography: a century old technology and the most commonly performed cardiac test. It is used to diagnose heart attacks, heart rhythm problems and operates as the gateway testing for patients undergoing cardiac evaluation. Myocardial infarction, or heart attacks, affect almost 800,000 Americans yearly [7] with time to treatment being the most important factor in recovery and therapy. We show in this paper that we are able to localize and detect myocardial infarctions at an accuracy above 99% by applying our system to the PTB database.
有多种方式用于诊断心脏异常,包括各种侵入性和非侵入性检查。患者可能会接受多次检查,以牺牲患者的风险和对夫妇的成本为代价,发展到更具侵入性的方法。通过机器学习和算法处理我们的专有软件,healtho希望提高心电图的准确性:这是一项有一个世纪历史的技术,也是最常用的心脏测试。它用于诊断心脏病发作,心律问题,并作为接受心脏评估的患者的门户测试。心肌梗塞或心脏病发作每年影响近80万美国人[7],治疗时间是恢复和治疗的最重要因素。我们在论文中表明,通过将我们的系统应用于PTB数据库,我们能够以99%以上的准确率定位和检测心肌梗死。
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引用次数: 0
The Research of Gait Recognition Based on High Dynamic Force Sensing Resistor 基于高动态力感电阻的步态识别研究
Peng Yang, Xiaodong Cai, Yanli Geng, Lingling Chen
The human gait contains the information of lower limb movement posture. Gait recognition and analysis can provide control information for lower limb rehabilitation robots. In different gait phases, the position of the foot touching the ground is different. Therefore, gait classification can be performed according to plantar pressure. This study investigated the changes in plantar pressure information during human lower limb walking. Firstly, the STM32 single-chip microcomputer is used to collect the plantar pressure information detected by the high dynamic force sensing resistor(HD-FSR); secondly, the collected information is transmitted to the upper computer through Bluetooth; finally, all kinds of gait phases pressure features are analyzed and classified. Since the two constant parameters in the Support Vector Machine(SVM) classification algorithm have a great influence on the classification effect, a SVM classification algorithm based on the Particle Swarm Optimization(PSO) is proposed to realize the recognition of different phases.
人的步态包含了下肢运动姿态的信息。步态识别与分析可以为下肢康复机器人提供控制信息。在不同的步态阶段,足部接触地面的位置是不同的。因此,可以根据足底压力进行步态分类。本研究探讨了人类下肢行走过程中足底压力信息的变化。首先,利用STM32单片机采集高动态力敏电阻(HD-FSR)检测的足底压力信息;其次,将采集到的信息通过蓝牙传输到上位机;最后,对步态各阶段压力特征进行了分析和分类。针对支持向量机(SVM)分类算法中两个常量参数对分类效果影响较大的问题,提出了一种基于粒子群优化(PSO)的支持向量机分类算法,实现对不同阶段的识别。
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引用次数: 0
Image Approach to Speech Recognition on CNN CNN语音识别的图像方法
M. Musaev, Ilyos Khujayorov, M. Ochilov
In this paper has been discussed about speech recognition using spectrogram images and deep convolution neural network(CNN) of Uzbek spoken digits. Spectrogram images from speech signal were generated and it were used for deep CNN training. Presented CNN model contains 3 convolution layers and 2 fully connected layers that discriminative features can be divided and estimated of spectrogram images by those layers. In current research period, dataset of Uzbek spoken digits were made and in based on presented CNN model they were trained. Testing results shows that, proposed approach for Uzbek spoken digits classified 100% accuracy.
本文讨论了利用乌兹别克语语音数字的频谱图图像和深度卷积神经网络(CNN)进行语音识别。从语音信号中生成频谱图图像,并将其用于CNN深度训练。所提出的CNN模型包含3个卷积层和2个全连通层,这些全连通层可以划分和估计光谱图图像的判别特征。在目前的研究阶段,制作了乌兹别克语语音数据集,并基于所提出的CNN模型对其进行训练。测试结果表明,所提出的方法对乌兹别克语语音数字的分类准确率达到100%。
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引用次数: 19
Diagnosing Clinical Manifestation of Apathy Using Machine Learning and Micro-facial Expressions Detection 利用机器学习和微面部表情检测诊断冷漠的临床表现
Antoun Yaacoub, Z. Assaghir, S. Makki, Radwan Almokdad
Apathy is a behavioral and personality change and is generally defined as a loss of motivation. In this study, we will explore the detection of apathy in two phases. An apathy detection phase, and relevant features identification phase. In the first one, we apply micro-facial expressions detection systems and counter for the purpose of diagnosing clinical manifestation of apathy from a video for Lebanese citizens. The method works by applying Histogram of Oriented Gradients (HOG) as a feature descriptor on video dataset of spontaneous micro facial movements. Micro-facial expressions appear by video recording participants reacting to emotional stimulating COPE cards. Results are compared to Lille Apathy Rating Scale LARS scores. Kappa agreement was calculated to be 95.96% showing the proposed classification method has a high accuracy of estimation. In a second phase, we aim to identify the demographics and habits that might be affecting the manifestation of apathy using machine leaning algorithms. A statistical model is built based on the results to identify the characteristics that affect the manifestation of apathy by analyzing the data and making a statistical description. Using a sample of 470 participants, we base our results on the decision tree (CART) combined with logistic regression. Finally, we found that insomnia, genetic background and stress are the most important features that influence the manifestation of apathy, with an accuracy of 96.7%.
冷漠是一种行为和性格的改变,通常被定义为失去动力。在本研究中,我们将从两个阶段探讨冷漠的检测。一个冷漠检测阶段,以及相关特征识别阶段。在第一篇文章中,我们应用微面部表情检测系统和计数器来诊断黎巴嫩公民视频中冷漠的临床表现。该方法将定向梯度直方图(Histogram of Oriented Gradients, HOG)作为特征描述符应用于面部微运动视频数据集。通过视频记录参与者对情绪刺激的COPE卡片的反应,可以看到微面部表情。结果与Lille冷漠评定量表(LARS)评分进行比较。Kappa一致性为95.96%,表明所提出的分类方法具有较高的估计精度。在第二阶段,我们的目标是使用机器学习算法确定可能影响冷漠表现的人口统计数据和习惯。在此基础上建立统计模型,通过对数据的分析和统计描述,找出影响冷漠表现的特征。使用470参与者的样本,我们基于决策树(CART)结合逻辑回归的结果。最后,我们发现失眠、遗传背景和压力是影响冷漠表现的最重要特征,准确率为96.7%。
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引用次数: 2
Procedural Animation of Aurora and its Optimization for Keyframe Animation 极光过程化动画及其关键帧动画优化
Tomokazu Ishikawa, Ryota Nakazato, I. Matsuda
There have been many studies regarding visual simulations that consider the characteristic movement of auroras. We have proposed a method of generating animation of auroras in the desired form and in the desired location visualized by the users. This study is based on the method proposed by Kojima et. al [5], in which shape control is performed comparatively easily through parameter adjustment. With this method, an artificial 2D distributed simulation of auroras, comprised of inflow points for charged particles flowing from space, has been produced. The curtain-shaped movement of auroras can be reproduced by applying a kinetic model using an electromagnetic field calculation and a fluid calculation within the simulation space. We can see that the reproduction of aurora-specific movement is dependent on the initial value of the current volume flowing from the various flow points. In this way, we attempted to control the shape of the desired aurora by controlling the current flow. In this study, we extracted two frames from the live-captured aurora video, and, set the initial distribution and target distribution of the aurora by reproducing the respective aurora distributions in 3D. As the respective distributions feature flow limits of charged particles forming an aurora 100 km above the ground, and many aurora video images often capture the horizon, we set the camera position as the point of origin and calculated the world coordinates for the lowest section of the aurora. A genetic algorithm was used to optimize the current flows. We set the cost function as the difference between the electric potential of the target shape and the electric potential based on the simulation results for the coordinates of each flow point. In addition, the number of searched parameters were reduced, assuming that the current distribution flowing to each flow point changes along with the initial shape functionally by expanding this function in a Fourier series, General shape control made possible through optimization. In the future works, we aim to increase control accuracy and gain the ability to control complex shapes.
有许多关于视觉模拟的研究考虑了极光的特征运动。我们提出了一种以用户可视化的期望形式和期望位置生成极光动画的方法。本研究基于Kojima等人[5]提出的方法,该方法通过参数调整比较容易实现形状控制。利用这种方法,已经产生了一个由空间带电粒子流入点组成的人工二维分布极光模拟。极光的幕状运动可以通过在模拟空间内应用电磁场计算和流体计算的动力学模型来再现。我们可以看到,极光特定运动的再现取决于从各个流点流出的当前体积的初始值。通过这种方式,我们试图通过控制电流来控制想要的极光的形状。在本研究中,我们从实时捕获的极光视频中提取两帧,并通过三维再现各自的极光分布来设置极光的初始分布和目标分布。由于各自的分布特征是带电粒子在地面以上100公里处形成极光的流动极限,并且许多极光视频图像经常捕捉到地平线,因此我们将相机位置设置为原点,并计算极光最低部分的世界坐标。采用遗传算法对电流进行优化。我们将代价函数设为目标形状的电势与基于仿真结果的各流点坐标的电势之差。此外,减少了搜索参数的数量,假设流向各流点的电流分布随初始形状函数变化,将该函数展开为傅里叶级数,通过优化使一般形状控制成为可能。在未来的工作中,我们的目标是提高控制精度,并获得控制复杂形状的能力。
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引用次数: 0
Automatic Implementation of Control Flow Error Detection Techniques 控制流错误检测技术的自动实现
J. Vankeirsbilck, H. Hallez, J. Boydens
Modern embedded systems are prone to erroneous bit-flips introduced in its hardware by external disturbances such as alpha particles, electromagnetic interference or intentional external attackers. In order to protect embedded systems against these disturbances, a wide variety of software-implemented detection techniques have been proposed, a.o. by the authors of this paper. Implementing those techniques, however, can be arduous and error-prone since they have to be implemented in low-level code, e.g. assembly. To overcome this problem we propose a compiler extension, in the form of a plugin, that can automatically add any supported technique to the low-level code of the target program. We discuss the internal working of our compiler extension and conclude with a demonstration using an example program and validate the effectiveness of the introduced countermeasures by running a fault injection campaign.
现代嵌入式系统容易因外部干扰(如α粒子、电磁干扰或有意的外部攻击者)而导致硬件出现错误的位翻转。为了保护嵌入式系统免受这些干扰,本文作者提出了各种各样的软件实现检测技术。然而,实现这些技术可能是艰巨而容易出错的,因为它们必须在低级代码中实现,例如汇编。为了克服这个问题,我们提出了一个编译器扩展,以插件的形式,它可以自动将任何支持的技术添加到目标程序的低级代码中。我们将讨论编译器扩展的内部工作,最后使用示例程序进行演示,并通过运行故障注入活动验证所引入的对策的有效性。
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引用次数: 5
All-encompassing Review of Biometric Information Protection in Fingerprints Based Steganography 基于指纹隐写术的生物特征信息保护综述
M. M. Hashim, Ahmed Kamal Mohsin, M. Rahim
In ascertaining the authenticity of a person's identity, the techniques that utilises Biometric Technology and its vital aspects and attributes are essential in endorsing this endeavour. Transversing the years, identification through biometric means has heightened much attention with regards to its susceptibility to assaults whilst information are being transferred. Thus, there is a dire need for the development for a safeguarding means. Steganography and watermarking methods are adopted towards the enhancement of biometric information secureness. Watermarking entails the embedding of data within file that carries the data, in safeguarding intellectual property rights and copyrights that involves music, video or image files. Meanwhile, steganography entails the concealment of data. This research puts forward an all-encompassing review pertaining the latest steganography methods that has been implemented to protect the biometric fingerprints information up-to-date. This review categorizes the fingerprint system into various sections, inclusive of methods for extracting features and matching procedure.
在确定一个人身份的真实性时,利用生物识别技术及其重要方面和属性的技术对于支持这一努力至关重要。多年来,通过生物识别手段进行身份识别在信息传输过程中引起了人们对其易受攻击的关注。因此,迫切需要开发一种保护手段。采用隐写和水印等方法增强生物特征信息的安全性。水印需要将数据嵌入到承载数据的文件中,以保护涉及音乐、视频或图像文件的知识产权和版权。同时,隐写术需要隐藏数据。本研究对保护生物指纹信息的最新隐写技术进行了全面的综述。本综述将指纹系统分为不同的部分,包括提取特征和匹配过程的方法。
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引用次数: 5
Lexisearch for Modeling Pushbroom Imaging Systems 为推扫帚成像系统建模的词典搜索
S. Koduri
The present study aims at exploiting lexicographic search(lexi-search in short) technique for modeling push broom imaging systems on board a spacecraft. Conventional techniques use a full force rigorous orbital photogrammetric model adopting iterative least squares techniques with partial derivatives of adjustment equations involving Taylor's series approximation. The proposed lexi-search technique is presented to overcome the general objection of handling rational polynomials with least square theory. The study illustrates this is excellent alternative to many bundled adjustment processes in use for camera calibration, geometric rectification, and 3D rendering.
本研究旨在利用词典搜索(简称词典搜索)技术对航天器上的推扫帚成像系统进行建模。传统的技术使用全力严格轨道摄影测量模型,采用迭代最小二乘技术,对涉及泰勒级数近似的平差方程进行偏导数。为了克服用最小二乘理论处理有理多项式的普遍缺点,提出了一种lexo搜索技术。该研究表明,这是用于相机校准,几何校正和3D渲染的许多捆绑调整过程的优秀替代方案。
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引用次数: 0
Study on Medical Imaging Reports Tagging Extraction Based on Bi-LSTM + CRF 基于Bi-LSTM + CRF的医学影像报告标注提取研究
Jiyun Li, Kaihua Li
As an important information carrier for hospital to record medical activities for patients, medical imaging report contains a large amount of technical terms and medical knowledge. In order to automatically generate computer-aided diagnosis reports, it is necessary to extract effective information from medical image reports, so as to reduce the pressure of professional physicians and better serve clinical decision-making. This paper mainly focuses on mammography medical imaging reports, analyzes the structure and contents of the reports, and deals with the imaging reports using the machine learning model, called Bi-LSTM + CRF (Bidirectional Long Short Term Memory with a Conditional Random Fields layer), in order to extract tags of the lesion, such as the position, size and shape in the imaging reports. The experimental results achieved satisfactory effort.
医学影像报告是医院记录患者医疗活动的重要信息载体,它包含了大量的专业术语和医学知识。为了自动生成计算机辅助诊断报告,有必要从医学图像报告中提取有效信息,以减轻专业医生的压力,更好地为临床决策服务。本文主要针对乳腺x线摄影医学影像报告,对报告的结构和内容进行分析,并利用Bi-LSTM + CRF (Bidirectional Long - Short Term Memory with a Conditional Random Fields layer)机器学习模型对影像报告进行处理,提取影像报告中病灶的位置、大小、形状等标签。实验结果取得了满意的效果。
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引用次数: 0
A Combination Method of Deep Learning Speech Separation and Independent Vector Analysis on Multi-channel Source Separation 一种深度学习语音分离与独立向量分析相结合的多通道源分离方法
Chunpeng Wang, Jie Zhu
Multi-channel blind source separation problem is a difficult but commonly met task in daily life. How to separate every target signals well using several observed signals fascinates hundreds of researchers to study on it, especially when the input channels are less than output channels. In this paper, authors analyze the characteristics of different BSS methods and propose a new method to solve under-determined multi-channel source separation problem. The proposed method has a combination structure of deep learning model and independent component analysis algorithm. Comparisons and evaluations show that using proposed method in multichannel source separation boosts separation effect to a certain degree.
多通道盲信源分离问题是日常生活中经常遇到的难题。如何利用多个观测信号很好地分离出每个目标信号,特别是在输入通道小于输出通道的情况下,是众多研究者研究的热点。本文分析了各种BSS方法的特点,提出了一种解决欠定多信道分离问题的新方法。该方法采用深度学习模型和独立分量分析算法相结合的结构。比较和评价表明,采用该方法进行多通道源分离,在一定程度上提高了分离效果。
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引用次数: 0
期刊
Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control
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