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8th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2019

作者： Lin, Xiang Liao, Xiangwen Xu, Tong Pian, Wenjing Wong, Kam-Fai College of Mathematics and Computer Science Fuzhou University Fuzhou China Anhui Province Key Laboratory of Big Data Analysis and Application School of Computer Science and Technology University of Science and Technology of China Hefei China The Chinese University of Hong Kong Sha Tin Hong Kong

ISBN: (纸本)9783030322359

Automatic rumor detection for events on online social media has attracted considerable attention in recent years. Usually, the events on social media are divided into several time segments, and for each segment, corresponding text will be converted as vectors for various neural network models to detect rumors. During this process, however, only sentence-level embedding has been considered, while the contextual information at the word level has been largely ignored. To address that issue, in this paper, we propose a novel rumor detection method based on a hierarchical recurrent convolutional neural network, which integrates contextual information for rumor detection. Specifically, with dividing events on social media into time segments, recurrent convolution neural network is adapted to learn the contextual representation information. Along this line, a bidirectional GRU network with attention mechanism is integrated to learn the time period information via combining event feature vectors. Experiments on real-world data sets validate that our solution could outperform several state-of-the-art methods. © 2019, Springer Nature Switzerland AG.

关键词： Convolution

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Classification of Cognitive Ability of Healthy Elderly Individuals Using Resting-State Functional Connectivity Magnetic Resonance Imaging and An Extreme Learning Machine

Research Square

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Research Square 2021年

作者： Yang, Zekun Ge, Manling Abdelkader, Nasreddine Belkacem Fu, Xiaoxuan Zhang, Qirui Chen, Shenghua Xie, Chong Song, Zibo Chen, Chao State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Hebei Province Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin300130 China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain15551 United Arab Emirates Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine General Hospital of Eastern Theater Nanjing210002 China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin300003 China

Purpose Quantitative determination of the correlation between cognitive ability and functional biomarkers in the elderly brain is essential. To identify biomarkers associated with cognitive performance in the elderly, this study combined an index model specific for resting-state functional connectivity (FC) magnetic resonance imaging (fcMRI) with a supervised machine learning method. Methods Performance scores on conventional cognitive test batteries and MRI data were obtained for 98 healthy elderly individuals and 90 healthy youth from two public databases. Based on the test scores, the elderly cohort was categorized into two groups: excellent and poor. An fcMRI index model was constructed for each elderly individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using the fcMRI indexes. To confirm the effectiveness of constructed model, the fcMRI indexes of these brain areas were used as feature matrix inputs for training an extreme learning machine. Classification accuracy was then tested in separate groups and confirmed by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy elderly individuals according to frontal lobe, temporal lobe, and parietal lobe FC values with a mean accuracy of 83.5%, which is substantially higher than that achieved using conventional correlation analysis. Conclusion This fcMRI classification study may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms. © 2021, CC BY.

关键词： Magnetic resonance imaging

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Adaptive Dynamic Surface Control of Constrained Nonlinear Systems

Adaptive Dynamic Surface Control of Constrained Nonlinear Sy...

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第32届中国控制与决策会议

作者： Ailiang Xing Biao Song Yixin Yin School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Demonstration and Research Department of Network Information System Beijing Institute of Computer Application

This paper presents an adaptive dynamic surface control for uncertain nonlinear strict feedback systems with constraints on both input and *** technology is employed in the controller *** performance method with asymmetric barrier Lyapunov function(BLF) is used to deal with the output *** input saturation is solved by using the Nussbaum *** dynamic surface control(DSC) technique is employed to reduce the complexity of the virtual *** is illustrated that all closed-loop signals are semi-global uniformly ultimately bounded(SGUUB).Finally,a simulation example proves the proposed results.

关键词： Input saturation Output constraints Nussbaum function Dynamic surface control

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Big data driven product design: A survey

arXiv

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arXiv 2021年

作者： Quan, Huafeng Li, Shaobo Zeng, Changchang Wei, Hongjing Hu, Jianjun College of Big Data and Statistics Guizhou Universify of Finance and Economics Guiyang550050 China State Key Laboratory of Public Big Data Guizhou University Guiyang550050 China Chengdu Institute of Computer Application Chinese Academy of Sciences Chengdu610041 China School of Mechanical Engineering Guizhou Institute of Technology Guiyang550050 China Department of Computer Science and Engineering University of South Carolina ColumbiaSC29201 United States

With the improvement of living standards, user requirements of modern products are becoming increasingly more diversified and personalized. Traditional product design methods can no longer satisfy the market needs due to their strong subjectivity, small survey scope, poor real-time data, and lack of visual display, which calls for the development of big data driven product design methodology. Big data in the product lifecycle contains valuable information for guiding product design, such as customer preferences, market demands, product evaluation, and visual display: online product reviews reflect customer evaluations and requirements;product images contain information of shape,color, and texture which can inspire designers to get initial design schemes more quickly or even directly generate new product images. How to efficiently collect product design related data and exploit them effectively during the whole product design process is thus critical to modern product design. This paper aims to conduct a comprehensive survey on big data driven product design. It will help researchers and practitioners to comprehend the latest development of relevant studies and applications centered on how big data can be processed, analyzed, and exploited in aiding product design. We first introduce several representative traditional product design methods and highlight their limitations. Then we discuss current and potential applications of textual data, image data, audio data, and video data in product design cycles. Finally, major deficiencies of existing data driven product design studies and future research directions are summarized. We believe that this study can draw increasing attention to modern data driven product design. © 2021, CC BY-NC-SA.

关键词： Product design

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Superior Performance of ZnGaO Solar-Blind Photodetectors by Implementing TFT Structure and Tunable ZNO Cycle Ratio

SSRN

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SSRN 2024年

作者： Fan, Hui-Chen Wang, Chen Xu, Yi-Hong Fan, Teng-Min Huang, Pao-Hsun Ruan, Yu-Jiao Wu, Tingzhu Kuo, Hao-Chung Wuu, Dong-Sing Lai, Feng-Min Lien, Shui-Yang Xiamen Key Laboratory of Development and Application for Advanced Semiconductor Coating Technology School of Opto-Electronic and Communication Engineering Xiamen University of Technology Xiamen361024 China School of Ocean Information Engineering Jimei University Jimei District Fujian Xiamen361021 China National Measurement and Testing Center for Flat Panel Display Industry Xiamen Institute of Measurement and Testing Xiamen361024 China National Integrated Circuit Industry and Education Integration Innovation Platform Department of Electronic Science Xiamen University Xiamen361005 China Department of Photonics Graduate Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan Department of Biomedical Engineering Da-Yeh University Changhua51591 Taiwan

In this study, plasma enhanced atomic layer deposition was used to prepare ZnGaO thin films with different ZnO cycle ratios from 0% to 50%, which were employed to fabricate the MSM-type and TFT-type solar-blind photodetector. The properties of the films and the performance of the solar blind photodetector are greatly affected by the ZnO cycle ratio. Appropriate Zn doping content decreases the ratio of oxygen vacancies and Zn interstitials in Ga2O3, while excessive Zn doping degrades the quality of the film. Compared to MSM-type photodetector, an obviously improved performance of ZnGaO TFT-type photodetector has been observed due to its self-amplified photocurrent and the reduced dark current controlled by gate voltage. At a ZnO cycle ratio of 40%, a superior performance of TFT-type solar-blind photodetector with an ultra-low dark current ~4.5×10-13 A, an excellent light switching ratio ~2.2×107, and an outstandingly high sensitivity ~34.31 A/W has been obtained. These results demonstrate that the incorporation of Zn dopants can effectively modulate the performance of Ga2O3 TFT-type photodetector providing a great perspective for cost-effective and high-performance solar-blind PDs. © 2024, The Authors. All rights reserved.

关键词： Zinc oxide

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An Energy Efficient Carry-Free Inner Product Unit

An Energy Efficient Carry-Free Inner Product Unit

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2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019

作者： Yan, Wen Ercegovac, Milos D. Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China University of California Computer Science Department Los AngelesCA United States

ISBN: (纸本)9781728123455

An energy efficient truncated inner product unit is proposed in this paper. The proposed unit is pipelined and processes the m pairs of n-bit operands in serial, so that only one unit is required and it can be reused in each recurrence. Truncated inner product is produced so that no accumulation is needed for the lower part. The array reduction unit is bit-level pipelined to improve throughput and reduce the initial delay. A two-level [4:2] adder is proposed to accumulate redundant vectors with non-uniform input arrival. The proposed inner product is compared with other truncated inner product units using fully merged arithmetic, partially merged arithmetic and the counter based inner product for different precision and vector length. Our proposed inner product unit has significant reduction in area, power and energy. © 2019 IEEE.

关键词： Pipelines

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Reverse-engineering bar charts using neural networks

arXiv

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arXiv 2020年

作者： Zhou, Fangfang Zhao, Yong Chen, Wenjiang Tan, Yijing Xu, Yaqi Chen, Yi Liu, Chao Zhao, Ying School of Computer Science and Engineer Central South University Changsha China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business University Beijing China Institute of Systems Engineering Academy of Military Sciences Beijing China Rail Data Research and Application Key Laboratory of Hunan Province Changsha China

Reverse-engineering bar charts extracts textual and numeric information from the visual representations of bar charts to support application scenarios that require the underlying information. In this paper, we propose a neural network-based method for reverse-engineering bar charts. We adopt a neural network-based object detection model to simultaneously localize and classify textual information. This approach improves the efficiency of textual information extraction. We design an encoder–decoder framework that integrates convolutional and recurrent neural networks to extract numeric information. We further introduce an attention mechanism into the framework to achieve high accuracy and robustness. Synthetic and real-world datasets are used to evaluate the effectiveness of the method. To the best of our knowledge, this work takes the lead in constructing a complete neural network-based method of reverse-engineering bar charts. Copyright © 2020, The Authors. All rights reserved.

关键词： Reverse engineering

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CS-Net: A Two-Step Epithelium Tissue Segmentation Regression Network with CS-Gate Attention on Histology Images

SSRN

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SSRN 2022年

作者： Gong, Zhengze Pan, Xipeng Han, Chu Qiu, Bingjiang Zhao, Bingchao Liu, Yu Chen, Xinyi Liu, Wenbin Chen, Zhihua Lu, Cheng Liu, Zaiyi Fang, Gang Institute of Computing Science and Technology Guangzhou University Guangzhou510006 China Department of Radiology Guangdong Provincial People’s Hospital Guangdong Academy of Medical Sciences Guangzhou510080 China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong Provincial People’s Hospital Guangdong Academy of Medical Sciences Guangzhou510080 China Guangdong Cardiovascular Institute Guangdong Provincial People’s Hospital Guangdong Academy of Medical Sciences Guangzhou510080 China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China

Background and Objective: The segmentation of oropharyngeal epithelium tissue within Haematoxylin&Eosin(HE)-stained pathological images is of great clinical significance for the pathological analysis and diagnosis. However, due to the imperfection of staining, staining fainting, or variations between staining methods in different labs, the contrast between epithelium and stroma may not be obvious in the HE-stained *** and methods: To address these challenges, we propose a two-step method, including a stain-style transfer step and a threshold segmentation step. In the first step, we propose a stain-style transfer network named CS-Net, together with our proposed attention module named CS-Gate, to convert the HE-stained image into an Immunohistochemistry (IHC)-stained image, aiming to enhance the appearance of epithelial tissue. In the second step, we perform threshold segmentation on the synthetic IHC-stained image to finally obtain a binary mask of oropharyngeal epithelium ***: We conduct experiments on Oropharyngeal Cancer Tissue-Microarray Image dataset, and the results show that CS-Net can generate a more precise binary mask than UNet-based segmentation networks(achieving an accuracy of 92.48%), while restoring colors and details better than general GAN-based networks (about 10% higher in Structural Similarity). Then we use Breast Cancer Cases (BCSS) public dataset as external validation, and find out that CS-Net has a stronger generalization capability. The code of CS-Net is available at https://***/frankie98kung/CS-Net. © 2022, The Authors. All rights reserved.

关键词： Tissue

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An Ultra-compact Broadband TE-pass Nanofocusing Structure

An Ultra-compact Broadband TE-pass Nanofocusing Structure

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Kejian Zhu Xu Pengfei Pengfei Sun Xingpeng Liu Haiou Li Zhiping Zhou Nano-optoelectronics Frontier Center of Ministry of Education Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic Technology Guilin China

We propose a broadband structure which integrates polarization and nanofocusing functions into a single device with 3.8x4 μm 2 footprint. The bandwidth is over 200 nm with insert loss (IL) smaller than 1.68 dB. ... 详细信息

ISBN: (数字)9781943580828

ISBN: (纸本)9781728176567

关键词： Bandwidth Nanoscale devices Optical fiber communication Broadband communication System-on-chip Photonics Periodic structures

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Predicted high-temperature superconductivity in rare earth hydride ErH2at moderate pressure

arXiv

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arXiv 2022年

作者： Liu, Yiding Fan, Qiang Yang, Jianhui Wang, Lili Zhang, Weibin Yao, Gang College of Mathematics and Physics Leshan Normal University Leshan614004 China Institute of Atomic and Molecular Physics Sichuan University Chengdu610065 China School of New Energy Materials and Chemistry Leshan Normal University Leshan614004 China Institute of Computer Application China Academy of Engineering Physics Mianyang621900 China College of Physics and Electronics Information Yunnan Key Laboratory of Optoelectronic Information Technology Yunnan Normal University Kunming650500 China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai200240 China

Hydrides offer an opportunity to study high-temperature (Tc) superconductivity at experimentally achievable pressures. However, they remained extremely high. Using density functional theory calculations, herein we demonstrated that a newly rare earth hydride, namely bulk ErH2, could be superconducting with a Tcaround 80 K at 14.5 GPa. To date, the drived pressure is the lowest reported value for compressed hydrides. Besides superconductivity, Fermi Surface nesting and Kondo effect were manifested at this pressure. Intriguingly, due to Kondo destruction, superconductivity was prone to exist at 15 GPa. Under the rest of applied pressures, we also revealed a gap of band structure at 20 GPa on the background of normal metallic states. At 20 GPa, this compressed system could act as a host of superconductor being judged from a sharp jump of spontaneous magnetic susceptibility with an evanescent spin density of state at Fermi level along with the competition between spin density wave and superconductivity. Finally, electron pairing glue for ErH2at these three typical pressures was attributed to the antiferromagnetic spin fluctuation. Copyright © 2022, The Authors. All rights reserved.

关键词： Density functional theory

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