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arXiv 2023年

作者： Jiang, Yucheng Wu, Yangliu Zhang, Jinlei Wei, Jingxuan Peng, Bo Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore117583 Singapore Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China 8 Somapah Road Singapore487372 Singapore National Engineering Research Center of Electromagnetic Radiation Control Materials School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China

The search for two-dimensional multiferroic materials is an exciting yet challenging endeavor. Recently, Song et al. reported the exciting discovery of type-II multiferroic order in an antiferromagnetic (AFM) NiI2 single layer, and concluded the ferroelectric (FE) polarization induced by a helical magnetic order1. Their finding was presented from all-optical experimental evidence, based on the methods of second harmonic generation (SHG) and linear dichroism (LD). However, the all-optical characterizations alone cannot serve as unanimous evidence of the "FE" existence, particularly in conjunction with magnetic orders in a single-layer multiferroic. A main argument is that their observed SHG and LD signals may just be manifested from the magnetic-order induced breaking of spatial-inversion or time-reversal symmetry instead of FE order, and thus cannot endorse the finding of a single-layer multiferroic. Accurate measurements of magnetic and electric orders are very essential to make a reliable judgement of a multiferroic. With the device’s thickness approaching atomic scale, its magnetic or electrical signals will become too weak to be collected by traditional measurements2. Therefore, advanced all-optical probing methods have been © 2023, CC BY-NC-SA.

关键词： Harmonic generation

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite Systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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Ischemic Stroke Onset Time Classification Using Automated Deep Learning Assessment Based on Diffusion-Weighted Imaging

SSRN

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SSRN 2025年

作者： Zhao, Ying Meng, Heng Wang, Xing-Yue Ding, Yan Chi, Qi Han, Dong-Qian Qiu, Lin Zhang, Si-Qi Du, Pei-Jie Yan, Chao Zhang, Yu-Sheng Xu, An-Ding Yang, Zhen-Guo Fang, Jian-Sheng Department of Neurology and Stroke Center The First Affiliated Hospital of Jinan University Guangdong Province Guangzhou China Clinical Neuroscience Institute The First Affiliated Hospital of Jinan University Guangdong Province Guangzhou China Medical Imaging Center The First Affiliated Hospital of Jinan university Guangdong Province Guangzhou China The Research Institute of Trustworthy Autonomous Systems The Department of Computer Science and Engineering Southern University of Science and Technology Guangdong Province Shenzhen China The Research Development Institute Guangzhou Guangri Stock Co. Ltd. Guangdong Province Guangzhou China

Identifying the onset time is essential when determining the suitable treatment for acute ischemic stroke (AIS). Regrettably, a portion of ischemic strokes were wake-up strokes. The objective is to develop an artificial intelligence-driven deep learning (DL) model that can automatically evaluate diffusion-weighted imaging (DWI) to categorize the onset time of AIS. Between January 2009 and March 2023, our stroke center acquired DWI images from 421 patients diagnosed with AIS within a 24-hour window. Subsequently, these DWI image datasets were utilized to train nine DL models, employing automated image processing methodologies, aimed at identifying AIS patients within 3, 4.5, and 6 hours post-symptom onset. The predictive capabilities of the DL models were compared against the diagnostic accuracy of human interpretations of DWI- fluid-attenuated inversion recovery (FLAIR) mismatch. The receiver operating characteristic curve (AUC) of DWI-FLAIR mismatch from human readings in identifying patients within 3, 4.5 and 6 hours of symptom onset were 0.72, 0.75 and 0.61, respectively. The Squeeze-and-Excitation Residual Network model displayed the highest AUC of 0.91 in identifying patients within 3 hours of symptom onset. The Vision Transformer Hybrid model achieving the highest AUC of 0.85 in identifying patients within 4.5 hours of symptom onset. The 18-layer Residual Network model achieving the highest AUC of 0.84 in identifying patients within 6 hours of symptom onset. DL models utilizing DWI to determine the onset time of AIS patients demonstrate superior performance compared to human assessments, highlighting their potential for automated and rapid classification of stroke onset times. © 2025, The Authors. All rights reserved.

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Ethical Considerations in Explainable AI: Balancing Transparency and User Privacy in English Language-based Virtual Assistants

Ethical Considerations in Explainable AI: Balancing Transpar...

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： Franciskus Antonius Alijoyo S. Sandya Sneha Sri Purnachandra Rao Alapati Dilyorjon Yuldashev Ponni Valavan M Center for Risk Management and Sustainability Indonesia School of Business and Information Technology STMIK LIKMI Bandung Indonesia Krishna University Andhra Pradesh Prasad V Potluri Siddhartha Institute of Technology Kanuru Vijayawada Andhra Pradesh India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Artificial Intelligence and Data Science K.Ramakrishnan college of Engineering Trichy Tamil Nadu India

English Language-Based Virtual Assistants (ELB-VAs) are AI-powered systems designed to comprehend and respond to user queries in the English language, exemplified by virtual assistants like Siri or Alexa. The need for balancing transparency and user privacy in ELB-VAs is paramount due to their pervasive integration into daily life. Ensuring transparency imbues user trust, while safeguarding privacy addresses ethical concerns associated with personal data. Existing methods involve clear privacy policies, user-controlled data sharing settings, and encryption. However, drawbacks include user confusion and potential biases. To address these limitations, this study proposes a novel approach. Methodologically, it integrates pre-processing techniques such as lowercasing and tokenization, coupled with a Natural Language Understanding model. This model undergoes intent and entity recognition training, enhancing accuracy, and incorporates privacy-aware response generation, ensuring informative yet privacy-conscious interactions. The implementation of the study's results is carried out using Python tools, showcasing improved metrics and response times. This approach contributes to a more transparent and privacy-respecting user experience, aligning with evolving ethical norms and setting the stage for advancements in ELB-VA technology. This comprehensive exploration bridges existing gaps, emphasizing the ethical imperative of user-centric and privacy-aware AI interactions in ELB- VAs. The proposed NLU model exhibits a substantial increase in accuracy compared to other methods, with an impressive accuracy value of 99.1 % • On average, it outperforms the Random Forest and Decision Tree models by 15.7 percentage points, highlighting its superior predictive capabilities in the evaluated task. This comprehensive exploration aligns with evolving ethical norms and establishes a foundation for future advancements in ELB-VA technology.

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Optimal control for phase locking of synchronized oscillator populations via dynamical reduction techniques

arXiv

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arXiv 2025年

作者： Fujii, Narumi Nakao, Hiroya Department of Systems and Control Engineering Institute of Science Tokyo Tokyo152-8552 Japan Research Center for Autonomous Systems Materialogy Institute of Science Tokyo Kanagawa 226-8501 Japan

We present a framework for controlling the collective phase of a system of coupled oscillators described by the Kuramoto model under the influence of a periodic external input by combining the methods of dynamical reduction and optimal control. We employ the Ott-Antonsen ansatz and phase-amplitude reduction theory to derive a pair of one-dimensional equations for the collective phase and amplitude of mutually synchronized oscillators. We then use optimal control theory to derive the optimal input for controlling the collective phase based on the phase equation and evaluate the effect of the control input on the degree of mutual synchrony using the amplitude equation. We set up an optimal control problem for the system to quickly resynchronize with the periodic input after a sudden phase shift in the periodic input, a situation similar to jet lag, and demonstrate the validity of the framework through numerical simulations. © 2025, CC BY.

关键词： Optimal control systems

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2DSM vs FFDM: A computeraided diagnosis based comparative study for the early detection of breast cancer

2DSM vs FFDM: A computeraided diagnosis based comparative st...

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Expert Systems

作者： Raghavendra, U. Gudigar, Anjan Ciaccio, Edward J. Ng, Kwan Hoong Chan, Wai Yee Rahmat, Kartini Acharya, U. Rajendra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal576104 India Department of Medicine Columbia University Medical Center New York United States Department of Biomedical Imaging University of Malaya Kuala Lumpur Malaysia Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi599489 Singapore Department of Biomedical Engineering School of Science and Technology SUSS University Clementi599491 Singapore School of Medicine Malaysia

Purpose: Accurate and early detection of breast cancer using effective imaging modalities is an active area of research in medical image analysis. computeraided diagnosis (CAD) of breast cancer using digital mammograms may help in early diagnosis and can assist in maintaining patient health. The breast imaging reporting and data system (BIRADS) is widely used for risk assessment and classification grading in breast cancer screening. It contains seven different grading systems for breast cancer risk assessment. These range from grade 0 (incomplete) to grade 6 (proven malignancy). All other intermediate stages state the progression of risk. Methods: The current research results have shown that two-dimensional synthesized mammogram (2DSM) imaging and conventional full-field digital mammography (FFDM) are two important imaging modalities which can be used for screening breast cancer. To the best of our knowledge, there is no study which has yet compared the BIRADS discrimination power of 2DSM and FFDM imaging modalities. In this paper we present a novel CAD-based comparative study, using texton and gist for the characterization of breast cancer with 2DSM and FFDM imagery. Results: The developed method achieved an average performance of 92.9% accuracy using a probabilistic neural network classifier for FFDM images with tenfold crossvalidation. Hence, our proposed model showed that FFDM images are more effective than the 2DSM imaging modality in discriminating BIRADS grades. Conclusion: The obtained results confirmed that our method performed well in the early detection of breast cancer. Consequently, it can be used as a distinct system in rural hospitals. © 2021, John Wiley and Sons Inc. All rights reserved.

关键词： Medical imaging computer aided diagnosis Diseases Grading Hospitals Mammography Risk assessment Tomography X ray screens Breast cancer risk assessments Breast imaging reporting and data systems Digital breast tomosynthesis Early detection of breast cancer Full field digital mammography gist Probabilistic neural networks texton

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Quantum Secret Sharing Enhanced: Utilizing W States for Anonymous and Secure Communication

arXiv

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arXiv 2024年

作者： Li, Guo-Dong Cheng, Wen-Chuan Wang, Qing-Le Cheng, Long Mao, Ying Jia, Heng-Yue School of Control and Computer Engineering North China Electric Power University Beijing102206 China Key Lab of Information Network Security Ministry of Public Security Shanghai200031 China Department of Computer and Information Science Fordham University New York City10458 United States School of Information Central University of Finance and Economics Beijing102206 China Engineering Research Center of State Financial Security Ministry of Education Central University of Finance and Economics Beijing102206 China

Quantum secret sharing (QSS) is the result of merging the principles of quantum mechanics with secret information sharing. It enables a sender to share a secret among receivers, and the receivers can then collectively recover the secret when the need arises. To enhance the practicality of these quantum protocols, an innovative concept of quantum anonymous secret sharing (QASS) is advanced. In this paper, we propose a QASS protocol via W states, which can share secrets while ensuring recover-ability, recover-security, and recover-anonymity. We have rigorously evaluated our protocols, verifying their accuracy and fortifying their security against scenarios involving the active adversary. This includes considerations for dishonest receivers and non-receivers. Moreover, acknowledging the imperfections inherent in real-world communication channels, we have also undertaken an exhaustive analysis of our protocol’s security and effectiveness in a quantum network where some form of noise is present. Our investigations reveal that W states exhibit good performance in mitigating noise interference, making them apt for practical applications. © 2024, CC BY-NC-ND.

关键词： Quantum theory

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Quantum advantage for differential equation analysis

引用

Physical Review A 2022年第2期105卷 022415-022415页

作者： Bobak Toussi Kiani Giacomo De Palma Dirk Englund William Kaminsky Milad Marvian Seth Lloyd Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Giacomo De Palma Scuola Normale Superiore 56126 Pisa Italy QuEra Computing Boston Massachusetts 02143 USA Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Electrical and Computer Engineering Center for Quantum Information and Control University of New Mexico Albuquerque New Mexico 87131 USA

Quantum algorithms for differential equation solving, data processing, and machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. In this study, we demonstrate that, when combined, these difficulties solve one another. We show how the output of quantum differential equation solving can serve as the input for quantum data processing and machine learning, allowing dynamical analysis in terms of principal components, power spectra, and wavelet decompositions. To illustrate this, we consider continuous-time Markov processes on epidemiological and social networks. These quantum algorithms provide an exponential advantage over existing classical Monte Carlo methods.

关键词： Machine learning Quantum algorithms Quantum computation Markovian processes Numerical techniques

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Position-Dependent Snap Feedforward: A Gaussian Process Framework

arXiv

引用

arXiv 2022年

作者： van Haren, Max Poot, Maurice Portegies, Jim Oomen, Tom The Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands The Centre for Analysis Scientific Computing and Applications Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands The Delft Center for Systems and Control Delft University of Technology Delft Netherlands

Mechatronic systems have increasingly high performance requirements for motion control. The low-frequency contribution of the flexible dynamics, i.e. the compliance, should be compensated for by means of snap feedforward to achieve high accuracy. Position-dependent compliance, which often occurs in motion systems, requires the snap feedforward parameter to be modeled as a function of position. Position-dependent compliance is compensated for by using a Gaussian process to model the snap feedforward parameter as a continuous function of position. A simulation of a flexible beam shows that a significant performance increase is achieved when using the Gaussian process snap feedforward parameter to compensate for position-dependent compliance. © 2022, CC BY.

关键词： Flexible structures

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