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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Yang Yang Yi Yang Ling Zhang Sultana Rejina Jie Zhuang State Grid Xin Jiang Company Limited Electric Power Research Institute University of Electronic Science and Technology of China (UESTC) Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China (UESTC) Chengdu China Precision Measurement Radar System Technology Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9781665446006

As an important branch of array signal processing, robust adaptive beamforming (RAB) has been widely used in many fields. In the conventional robust adaptive beamformers, a common problem is that the estimated manifold vector of the signal of interest (SOI) may converge to the interference subspace. By using the data dependent constraints, such problem can be mitigated. In this paper, first we reconstruct the covariance matrices for the desired signal. Then a novel RAB is proposed in which the data dependent constraints are formed on the basis of the reconstructed signal covariance matrices. Moreover, the optimal solution to the proposed RAB can be found by the Lagrange multiplier methodology and the semi-definite generalized eigen- decomposition. Simulation results demonstrate the effectiveness of our proposed RAB.

关键词： Manifolds Degradation Interference cancellation Array signal processing Simulation Conferences Parallel processing

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, Computer Retrospective Study

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Modulation Signal Recognition Based on Feature Fusion and Residual CNN in Fractal Noise Background

Modulation Signal Recognition Based on Feature Fusion and Re...

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IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Di Chen Gang Xiong Baigang Huang Lijun Wang Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of Cetc Jiaxing China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Institute of Navigation and Sensing Shanghai Jiao Tong University China

ISBN: (纸本)9781665446006

In this paper, a modulated signal recognition method based on feature fusion and ResCNN (FF-ResCNN) under generalized fractal noise background is proposed. Firstly, in the feature extraction and fusion part, considering the robustness, anti-noise and interpretability of the features, the fusion feature vectors of generalized fractal spectrum, instantaneous feature and high-order cumulant feature are constructed. Secondly, in order to suppress the possible gradient and degradation problems, the ResCNN model is used to train and classify the fusion features when the CNN model is used to further collect the deep-level abstract features. Finally, feature extraction, feature fusion and classification experiments are carried out for nine modulated signals under two noise types (GWN and fractal noise). Experimental results show that in the case of generalized fractal noise, when SNR=0dB, the recognition accuracy of signal modulation type reaches 95.42%, which verifies the superiority of the proposed method. At the same time, the simulation analysis is carried out for different feature fusion schemes, which provides a valuable reference for feature combination optimization under different noise environment.

关键词： Degradation Deep learning Conferences Neural networks Modulation Feature extraction Fractals

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Pathfinding and Routing for Automated Driving in the Lanelet2 Map Framework

Pathfinding and Routing for Automated Driving in the Lanelet...

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International Conference on Intelligent Transportation

作者： Fabian Poggenhans Johannes Janosovits Intelligent Systems and Production Engineering FZI Research Center for Information Technology Karlsruhe Germany Institute of Measurement and Control Systems (MRT) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

In this paper we introduce the concept of routing and pathfinding, which is used by the Lanelet2 map framework for automated driving. While in conventional map frameworks the routing graph is explicitly predefined, Lanelet2 interprets it at runtime. This offers many advantages for automated driving, because it allows the map information to be viewed from different perspectives, such as other road users or for other traffic situations. We also analyze what information is typically required by routing applications in automated driving, how this affects the shape of the routing graph, and how this information can be extracted efficiently. The paper concludes with an overview of developments in high-definition maps. In our opinion, these are lagging behind progress in the other areas of automated driving. We hope that Lanelet2 continues to gain increasing acceptance in the community and thus helps to remedy this shortcoming.

关键词： Roads Routing Task analysis Junctions Shape Planning Data models

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Measuring System Of Internal Charges In Electron Irradiated Spacecraft’s Insulating Medium

Measuring System Of Internal Charges In Electron Irradiated ...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Yue Feng Xusong Tang Yanhui Han Science and Technology on Electromechanical Dynamic Control Laboratory School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Orient Institute of Measurement& Test Beijing China

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

The accumulation of internal charge in the insulating medium caused by the high-energy charged particles has been one of the important factors threatening the safety of spacecrafts. As the spacecraft's orbital flight time and flight height increase, the internally charged effect of its insulating medium becomes more and more serious. In this work, we designed an internal charge distribution measuring system for an insulating medium under electron irradiation, based on the acoustic pulse method. The system could measure the internal charge of the dielectric material without contacting between the sample and the excitation unit. Furthermore, the internal charge measurements were performed on three kinds of typical spacecraft insulation medium materials (polyimide (PI), low-density polyethylene (LDPE), and polytetrafluoroethylene (PTFE)) under electron irradiation. The internal charge and internal electric field distribution of the specimens were obtained. This system is more suitable for studying the internal charge accumulation behavior of spacecraft's insulating medium in space environment.

关键词： Radiation effects Polyimides Polyethylene Data processing Charge measurement

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Abnormal Behavior Detection Based on the Potential Field Forces in Surveillance Scenarios

Abnormal Behavior Detection Based on the Potential Field For...

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作者： Yong Qiang Shumin Fei Liuwen Li Key Laboratory of Measurement and Control of CSE(Ministry of Education) School of Automation Southeast University School of Computer Engineering Jinling Institute of Technology

In a social environment, there is a natural mutual force between people. This paper proposes a method for detecting group abnormal behavior based on the potential field method. The movement of a pedestrian is described as the movement towards the target under the combined action of several forces. Forces on pedestrians include the attractive force for themselves and the repulsive force between pedestrians. By calculating the resultant force between them, the behavior of pedestrians is judged according to a set threshold. It is verified through experiments on public data sets that our method has high accuracy and robustness.

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The Study of Pt Isolated Single Atoms Assistant for the Hydrodeoxygenation of Phenol Under Mild Conditions

SSRN

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SSRN 2022年

作者： Li, Xu Ma, Longlong Yan, Long Liu, Ziyue Liao, Yuhe Department of Thermal Science and Energy Engineering University of Science and Technology of China Hefei230026 China Key Laboratory of Energy Thermal Conversion and Process Measurement and Control of Ministry of Education School of Energy and Environment Southeast University Jiangsu Nanjing210096 China CAS Key Laboratory of Renewable Energy Guangzhou Institute of Energy Conversion Chinese Academy of Sciences Guangzhou510640 China

Catalytic hydrodeoxygenation (HDO) of oxygenated compounds under mild conditions is essential for chemical refining, which is always relied on improving hydrogenation activity or/and acid strength of catalytic system. Here, with the synthesis of functional TiO 2 (B) nanosheet, we developed a novel Pt/TiO 2 (B) catalyst for HDO of phenol. Through the synergistic effect of dispersed Pt isolated single atoms and nanoclusters, phenol was efficiently converted into cyclohexane without extra acid under 50 o C and atmospheric hydrogen. The catalytic diversity of two Pt species for C=O/C=C bonds leads to the formation of ketene/enol intermediates, as detected in the in-situ FT-IR tests. Due to the low C-O bond energy of enol intermediates, the HDO of phenol could be carried out at mild conditions through the implementable C-O bond cleavage of enol intermediates. This study provides a new understanding of green HDO process and a novel approach for HDO catalysts developing. © 2022, The Authors. All rights reserved.

关键词： Phenols

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Spatiotemporal characterization of laser pulse amplification in double-pass active mirror geometry

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High Power Laser Science and engineering 2020年第3期8卷 16-30页

作者： Tinghao Liu Qiang Liu Zhan Sui Mali Gong Xing Fu Key Laboratory of Photonic Control Technology(Tsinghua University) Ministry of EducationBeijing 100084China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084China Shanghai Institute of Laser Plasma China Academy of Engineering PhysicsShanghai 201800China

We present a spatiotemporal model of pulse amplification in the double-pass active mirror(AM)*** types of overlap condition are studied,and the spatiotemporal scaling under the four-pulse overlapping(4 PO)condition is fully characterized for the first time,by mapping the temporal and spatial segments of beam to the instantaneous gain ***,the influence of spatiotemporal overlaps on the amplified energy,pulse distortion and intensity profile is unraveled for both AM and zigzag *** model,verified by excellent agreement between the predicted and measured results,can be a powerful tool for designing and optimizing high energy multi-pass solid-state laser amplifiers with AM,zigzag and other geometries.

关键词： active mirror amplifier pulse overlap spatiotemporal characterization double-pass

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EmotionBox: a music-element-driven emotional music generation system using Recurrent Neural Network

arXiv

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arXiv 2021年

作者： Zheng, Kaitong Meng, Ruijie Zheng, Chengshi Li, Xiaodong Sang, Jinqiu Cai, Juanjuan Wang, Jie Key Laboratory of Noise and Vibration Research Institute of Acoustics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China School of Electronics and Communication Engineering Guangzhou University Guangzhou China National Environmental Protection Engineering and Technology Center for Road Traffic Noise Control Beijing China

With the development of deep neural networks, automatic music composition has made great progress. Although emotional music can evoke listeners’ different emotions and it is important for artistic expression, only few researches have focused on generating emotional music. This paper presents EmotionBox -an music-element-driven emotional music generator that is capable of composing music given a specific emotion, where this model does not require a music dataset labeled with emotions. Instead, pitch histogram and note density are extracted as features that represent mode and tempo respectively to control music emotions. The subjective listening tests show that the Emotionbox has a more competitive and balanced performance in arousing a specified emotion than the emotion-label-based method. Copyright © 2021, The Authors. All rights reserved.

关键词： Music

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Real-time watermark reconstruction for the identification of source information based on deep neural network

Real-time watermark reconstruction for the identification of...

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作者： Sinhal, Rishi Ansari, Irshad Ahmad Jain, Deepak Kumar Electronics and Communication Engineering PDPM Indian Institute of Information Technology Design and Manufacturing JabalpurMP482005 India Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

A novel deep neural network-based image watermarking method is presented to identify the source of digital data that is shared/forwarded on the internet using various messenger apps. The app that is used to share/communicate the image at the very first time is also identified in the proposed method. The ten-digit mobile number of the source (user) and identification data of particular messenger app (i.e. WhatsApp, Snapchat, Kik, Facebook messenger, etc.) is combined to get the text watermark signal. The part of the watermarksignal representing specific mobile-based messenger application is obtained by randomizing the Walsh orthogonal codes using secret keys. To embed the watermark, the host image (shared/forwarded) is divided into blocks of equal size and then, slantlet transform is applied on each block. To get high reliability, three copies of the source information (user and app) are embedded during watermark embedding. Watermark extraction is performed using trained multilayer deep neural network. Furthermore, an optimal block selection logic is used to get improved results for real-time applications. The method is examined against various signal-processing attacks and high robustness with significant imperceptibility is attained. The method is also found to be fast enough for real-time applications. The prime objective of identifying the first user (source) and the shared/forwarded status (app detection) is successfully accomplished. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Deep neural networks

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