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A Design of Software and Hardware System for Pre-hospital Emergency Treatment

Chinese Journal of Biomedical Engineering(English Edition) 2020年第3期29卷 1-9页

作者： Bingxu Ye Feng Chen Shaomin Ou Yang Xie Yaowen Chen The Key Lab of Digital Signal and Image Processing of Guangdong Shantou Guangdong 515063China Shantou University Medical College Shantou Guangdong 515041China The Second Affiliated Hospital of Shantou University Medical College Shantou Guangdong 515041China

This paper aims to improve the pre-hospital first-aid knowledge and pre-hospital first-aid success rate and optimize the pre-hospital emergency *** paper mainly discusses a comprehensive pre-hospital emergency system,which consists of the hardware part and software *** hardware is based on the international cardiopulmonary resuscitation guidelines,and a cardiopulmonary resuscitation(CPR)training auxiliary equipment is developed,which can be applied in pre-hospital first aid training to help people perform accurate chest *** software part is based on the WeChat applet platform to set up a pre-hospital first-aid dispatching system that connects callers and CPR *** software system effectively improves the pre-hospital CPR first-aid system and increases the rescue success rate of cardiac arrest patients.

关键词： Chest compression CPR Auxiliary equipment WeChat applet

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Robust change-point detection and segmentation in data streams

Robust change-point detection and segmentation in data strea...

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MILCOM, Military communications Conference

作者： G.A. Tsihrintzis C.L. Nikias Communication Systems Lab Department of Electrical Engineering University of Virginia Charlottesville VA USA Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA USA

We address the problem of robust detection of those points in time where the statistical properties of an observed time series change. This is a critical theoretical problem in modern statistical signal processing with significant applications in multiple access communication systems and segmentation of multimedia signals, as well as in hidden signal detection, fault detection and diagnosis. We develop new, robust algorithms which maintain a performance close to the corresponding optimum (maximum likelihood) algorithm in the entire class of symmetric, alpha-stable signals and noise. Our algorithms are illustrated via computer simulation, while application on real radar sea-clutter data corroborates our findings.

关键词： Signal processing algorithms Streaming media communication systems Multimedia systems Signal processing Signal detection Fault detection Fault diagnosis Noise robustness Change detection algorithms

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Controlling Expressivity using Input Codes in Neural Network based TTS

Controlling Expressivity using Input Codes in Neural Network...

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Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia)

作者： Xiaolian Zhu Lei Xie Xiao Chen Xiaoyan Lou Xuan Zhu Xingjun Tan Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi’an Hebei University of Economics and Business Shijiazhuang China Shaanxi Provincial Key Laboratory of Speech and Image Information Processing School of Computer Science Northwestern Polytechnical University Xi’an China Language Computing Lab Samsung R&D Institute of China Beijing China

ISBN: (纸本)9781538653128

This paper presents a study on the use of input codes in the neural network acoustic modeling for expressive TTS. Specifically, we use different kinds of input codes, augmented with the linguistic features, as the input of a BLSTM-based acoustic model, to control the expressivity of the synthesized speech. The input codes, in one-hot representation, include dialogue code, sentiment code and sentence position code. The dialogue code indicates whether the text is a dialogue or narration in an audiobook story. The sentiment code is obtained from a sentiment analysis tool, which labels each sentence as positive, negative and neutral. The sentence position code indicates the position of the sentence in the paragraph. We believe these codes are highly related to the expressiveness of the audiobook speech. Experiments on the data from the Blizzard Challenge 2017 demonstrate the effectiveness of the use of input codes in the neural network approach for expressive TTS.

关键词： Neural networks Linguistics Acoustics Hidden Markov models Speech synthesis Adaptation models Speech coding

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A survey on negative transfer

arXiv

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arXiv 2020年

作者： Zhang, Wen Deng, Lingfei Zhang, Lei Wu, Dongrui the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China the School of Microelectronics and Communication Engineering Chongqing University Chongqing400044 China

—Transfer learning (TL) utilizes data or knowledge from one or more source domains to facilitate the learning in a target domain. It is particularly useful when the target domain has very few or no labeled data, due to annotation expense, privacy concerns, etc. Unfortunately, the effectiveness of TL is not always guaranteed. Negative transfer (NT), i.e., leveraging source domain data/knowledge undesirably reduces the learning performance in the target domain, has been a long-standing and challenging problem in TL. Various approaches have been proposed in the literature to handle it. However, there does not exist a systematic survey on the formulation of NT, the factors leading to NT, and the algorithms that mitigate NT. This paper fills this gap, by first introducing the definition of NT and its factors, then reviewing about fifty representative approaches for overcoming NT, according to four categories: secure transfer, domain similarity estimation, distant transfer, and NT mitigation. NT in related fields, e.g., multi-task learning, lifelong learning, and adversarial attacks, are also discussed. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

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Controllable deoxyribonucleic acids sub-tile self-assembly by deoxyribonucleic acids strand displacement

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3774-3780页

作者： Wang, Yanfeng Zhao, Taotao Shi, Xiaolong Li, Mengmeng Cui, Guangzhao School of Electrical and Information Engineering Henan Key Lab of Information-Based Electrical Appliances Zhengzhou University of Light Industry Zhengzhou China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China

Here we report a controllable four DNA sub-tiles, self-assembling into 4-arm DNA tiles, under control of a DNA strand displacement based on DNA sequential circuit. The motif is encoded, compiled and simulated successively in Visual DSD software. The simulation results show that the four kinds of sub-tiles in the motif combine to their neighbors one after another with a certain time delay and finally form into 4-arm DNA tiles. The formation of the 4th arm of a 4-arm DNA tile indicates that all the 4-arm DNA tiles have been assembled, which implies high productivity of the 4-arm DNA tiles. We also analyze the time responses of the DNA sequence circuit by adjusting the concentration proportions of reactants and/or ordering bind and unbind rates of toeholds in simulation. These simulation results demonstrate that high concentration proportions of reactants and/or toeholds reacting at ascending order rates can shorten the time response more sharply than that low concentration proportion of reactants and/or in a descending order. The motif furthers the integration for DNA sub-tile self-assembly and DNA strand displacement. Copyright © 2015 American Scientific Publishers.

关键词： DNA

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Depth-Aware Video Frame Interpolation

Depth-Aware Video Frame Interpolation

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IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Wenbo Bao Wei-Sheng Lai Chao Ma Xiaoyun Zhang Zhiyong Gao Ming-Hsuan Yang Institute of Image Communication and Network Engineering Shanghai Jiao Tong University University of California Merced MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University

ISBN: (纸本)9781728132945

Video frame interpolation aims to synthesize nonexistent frames in-between the original frames. While significant advances have been made from the recent deep convolutional neural networks, the quality of interpolation is often reduced due to large object motion or occlusion. In this work, we propose a video frame interpolation method which explicitly detects the occlusion by exploring the depth information. Specifically, we develop a depth-aware flow projection layer to synthesize intermediate flows that preferably sample closer objects than farther ones. In addition, we learn hierarchical features to gather contextual information from neighboring pixels. The proposed model then warps the input frames, depth maps, and contextual features based on the optical flow and local interpolation kernels for synthesizing the output frame. Our model is compact, efficient, and fully differentiable. Quantitative and qualitative results demonstrate that the proposed model performs favorably against state-of-the-art frame interpolation methods on a wide variety of datasets. The source code and pre-trained model are available at .

关键词： Interpolation VIDEO FRAMES Occlusion Frame Object motion Optic Flow Source code FRAMES

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Robust stability clearance of flight control law based on global sensitivity analysis

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Journal of Applied Mathematics 2014年第1期2014卷

作者： Ou, Liuli Liu, Lei Dong, Shuai Wang, Yongji Key Lab of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

To validate the robust stability of the flight control system of hypersonic flight vehicle, which suffers from a large number of parametrical uncertainties, a new clearance framework based on structural singular value () theory and global uncertainty sensitivity analysis (SA) is proposed. In this framework, SA serves as the preprocess of uncertain model to be analysed to help engineers to determine which uncertainties affect the stability of the closed loop system more slightly. By ignoring these unimportant uncertainties, the calculation of can be simplified. Instead of analysing the effect of uncertainties on which involves solving optimal problems repeatedly, a simpler stability analysis function which represents the effect of uncertainties on closed loop poles is proposed. Based on this stability analysis function, Sobol's method, the most widely used global SA method, is extended and applied to the new clearance framework due to its suitability for system with strong nonlinearity and input factors varying in large interval, as well as input factors supjecting to random distributions. In this method, the sensitive indices can be estimated via Monte Carlo simulation conveniently. An example is given to illustrate the efficiency of the proposed method. © 2014 Liuli Ou et al.

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A Multi-input Deep Neural Network Framework for Non-invasive Detection of Anemia using Finger Nail images

A Multi-input Deep Neural Network Framework for Non-invasive...

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International Conference on Biosignals, images and Instrumentation (ICBSII)

作者： Krithika S Ajay Kumar Reddy Poreddy Thunakala Balakrishna Priyanka Kokil Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India Department of Electronics and Communication Engineering Advanced Signal and Image Processing (ASIP) Lab Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai

ISBN: (数字)9798350350951

ISBN: (纸本)9798350350968

Anemia, characterized by a deficiency in red blood corpuscles or hemoglobin, poses a significant global health challenge, particularly affecting vulnerable populations. Traditional diagnostic methods often involve invasive procedures, posing challenges in resource-limited settings. This study aims to explore non-invasive anemia detection using fingernail images and convolutional neural networks (CNNs) as a promising alternative to conventional diagnostic approaches. The study utilizes a dataset of fingernail images collected from hospitals in Ghana, comprising both anemic and non-anemic cases. The dataset undergoes preprocessing, including selective enhancement of red components, conversion to the CIElab color space, and feature extraction. A multi-input Deep Neural Network (DNN) framework employing pre-trained CNNs is proposed for anemia classification. The pre-trained CNN architectures include EfficientNet B1, EfficientNet B4, and MobileNet V3. The framework’s performance was assessed using two methodologies: The first involved random shuffling of the dataset, followed by division into training, testing, and validation sets, with evaluation metrics including Accuracy, Precision, F1 scores, and a Confusion Matrix. The second employed five-fold cross-validation, measured using accuracy. The evaluation of the proposed DNN framework using both of the methodologies indicates that EfficientNet B4 achieved the highest testing accuracy (97.87%), precision (97.88%), recall (97.87%), and F1 score (97.88%) and a cross-validation accuracy of 97.37% for the first and second methodologies respectively making it best fit for the proposed DNN framework. The findings demonstrate that the proposed framework yields promising results, especially under the second approach, and opens avenues for further exploration in transfer learning, fine-tuning of deep neural networks for multi-input feature integration, and cross-validation.

关键词： Training Accuracy Transfer learning Sociology Nails Quality assessment Convolutional neural networks

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Analysis of multiscale sign series entropy of the young and middle-aged electroencephalogram signals

Analysis of multiscale sign series entropy of the young and ...

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International Congress on image and Signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Fei Du Shitong Wang Jun Wang Jiafei Dai Fengzhen Hou Jin Li Image Processing and Image Communications Key Lab Nanjing Univ. of Posts & Telecomm Nanjing China Nanjing General Hospital of Nanjing Military Command Nanjing China School of Science China Pharmaceutical University Nanjing China College of Physics and Information Technology Shanxi Normal University Xian China

ISBN: (纸本)9781509037117

The physiological analysis of electroencephalogram (EEG) signals is of great significance in assessing the activity of the brain function and the physiological state. EEG is a means of clinical examination of brain diseases. Age is one of the important factors that affect the results of the EEG. EEG signal analysis is mainly to analyze the time series of the signal, multiscale entropy (MSE) analysis [1-3] is the method that used to analyze the finite length of the time series. Multiscale sign series entropy (MSSE) method is proposed for the analysis of EEG signals in the young and middle-aged. We use the proposed method to analyze the signals from several aspects of data length, word length, noise, multi scale etc. By analyzing the influence of these factors, we can still distinguish the EEG signals of different ages. Multiscale sign series entropy (MSSE) analysis algorithm can effectively separate the brain electrical signals from the young and middle aged, which is expected to have a certain reference value for the traditional pathological analysis of the EEG signals.

关键词： Electroencephalography Entropy Time series analysis Brain models Algorithm design and analysis Physiology

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Geometric Distance for Fast Micro-Expression Detection 20

Geometric Distance for Fast Micro-Expression Detection

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20th IEEE International Conference on communication Technology, ICCT 2020

作者： Lu, Hua Li, Dengwang Kpalma, Kidiyo Yang, Mingqiang Shandong Normal University Shandong Key Lab. of Med. Physics and Image Processing Shandong Provincial Engineering and Technical Center of Light Manipulations School of Physics and Electronics Jinan250358 China Ietr VAADER- Umr 6164 Univ Rennes Insa Rennes RennesF-35000 France Shandong University School of Information Science and Engineering Qingdao266237 China

ISBN: (纸本)9781728181417

In this paper, we propose a new model for micro-expression detection in videos in conjunction with a set of facial keypoints. The main contribution lies at the construction of geometric features extracted using the geometric distances between pairs of keypoints in different groups. The proposed geometric features-based micro-expression detection model requires a very low computation complexity and simultaneously attains highly accurate detection rates. We compare the proposed geometric features-based model to the existing state-of-the-art micro-expression detection and recognition models in three datasets, where the proposed method has achieved better, or at least comparably accurate results but requiring much less computation time. © 2020 IEEE.

关键词： Support vector machines

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