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2024 IEEE Photonics Conference, IPC 2024

作者： Zhang, Xuguang Zhou, Zixuan Guo, Yijun Zhuang, Minxue Jin, Warren Shen, Bitao Chen, Yujun Huang, Jiahui Hu, Weiwei Shu, Haowen Bowers, John E. Wang, Xingjun Chang, Lin University of California Santa Barbara Department of Electrical and Computer Engineering Santa BarbaraCA United States Peking University State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Beijing China Peking University Frontiers Science Center for Nano-Optoelectronics Beijing China

ISBN: (纸本)9798350361957

We demonstrate a high-coherence parallel integrated light source utilizing a self-injection locked microcomb and injection locking amplification. Our strategy exhibits a record high on-chip gain of 60 dB, nearly 0 dB noise factor, which enable more than 30 highly coherent channels in integrated photonics whose linewidths down to 10 Hz, power exceeding 20 dBm per line and a wall plug efficiency of 19%. © 2024 IEEE.

关键词： Photonic integrated circuits

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CNN-Based Breast Cancer Ultrasound Medical Image Recognition 6

CNN-Based Breast Cancer Ultrasound Medical Image Recognition

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Jin, Zexiong Zhang, Qichun Zhao, Jinhui School of Computer Science Ai and Electronics University of Bradford Bradford United Kingdom School of Creative and Digital Industries Buckinghamshire New University High Wycombe United Kingdom College of Electrical Engineering Zhejiang University of Water Resources & Electric Power Key Laboratory for Technology in Rural Water Mangmenet of Zhejiang Province Hangzhou310018 China

ISBN: (纸本)9798350356618

This paper proposes a novel data model for the recognition of medical images in breast cancer ultrasound examinations, based on convolutional neural networks (CNN). To validate the effectiveness of the proposed model, experiments were conducted on 765 data samples, and four evaluation metrics-accuracy, precision, recall, and F1 score-were calculated to analyse the classification performance of the trained model. The results indicate that the new CNN model achieves a minimum recognition accuracy of no less than 70% on the test set, demonstrating robust recognition performance and meeting the designed objectives. © 2024 IEEE.

关键词： Convolutional neural networks

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Near-Field Mobile Tracking: A Framework of Using XL-RIS Information

arXiv

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arXiv 2024年

作者： Wu, Tuo Pan, Cunhua Zhi, Kangda Yao, Junteng Ren, Hong Elkashlan, Maged Yuen, Chau The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom

This paper introduces a novel mobile tracking framework leveraging the high-dimensional signal received from extremely large-scale (XL) reconfigurable intelligent surfaces (RIS). This received signal, named XL-RIS information, has a much larger data dimension and therefore offers a richer feature set compared to the traditional base station (BS) received signal, i.e., BS information, enabling more accurate tracking of mobile users (MUs). As the first step, we present an XL-RIS information reconstruction (XL-RIS-IR) algorithm to reconstruct the high-dimensional XL-RIS information from the low-dimensional BS information. Building on this, this paper proposes a comprehensive framework for mobile tracking, consisting of a Feature Extraction Module and a Mobile Tracking Module. The Feature Extraction Module incorporates a convolutional neural network (CNN) extractor for spatial features, a time and frequency (T&F) extractor for domain features, and a near-field angles of arrival (AoAs) extractor for capturing AoA features within the XL-RIS. These features are combined into a comprehensive feature vector, forming a time-varying sequence fed into the Mobile Tracking Module, which employs an Auto-encoder (AE) with a stacked bidirectional long short-term memory (Bi-LSTM) encoder and a standard LSTM decoder to predict MUs’ positions in the upcoming time slot. Simulation results confirm that the tracking accuracy of our proposed framework is significantly enhanced by using reconstructed XL-RIS information and exhibits substantial robustness to signal-to-noise ratio (SNR) variations. © 2024, CC BY.

关键词： Convolutional neural networks

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Facile Semiconductor p-n Homojunction Nanowires with Strategic p-Type Doping engineering Combined with Surface Reconstruction for Biosensing Applications

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Nano-Micro Letters 2024年第10期16卷 15-30页

作者： Liuan Li Shi Fang Wei Chen Yueyue Li Mohammad Fazel Vafadar Danhao Wang Yang Kang Xin Liu Yuanmin Luo Kun Liang Yiping Dang Lei Zhao Songrui Zhao Zongzhi Yin Haiding Sun iGaN Laboratory School of MicroelectronicsUniversity of Science and Technology of ChinaHefei 230026People's Republic of China Department of Obstetrics and Gynecology The First Affiliated Hospital of Anhui Medical UniversityNo 218 Jixi RoadHefei 230022People's Republic of China Department of Electrical and Computer Engineering McGill University3480 University StreetMontrealQC H3A 0E9Canada Union Hospital Tongji Medical CollegeHuazhong University of Science and TechnologyNo 1277 Jiefang Ave.Wuhan 430022People's Republic of China

Photosensors with versatile functionalities have emerged as a cornerstone for breakthroughs in the future optoelectronic systems across a wide range of *** particular,emerging photoelectrochemical(PEC)-type devices have recently attracted extensive interest in liquid-based biosensing applications due to their natural electrolyte-assisted operating ***,a PEC-type photosensor was carefully designed and constructed by employing gallium nitride(GaN)p-n homojunction semiconductor nanowires on silicon,with the p-GaN segment strategically doped and then decorated with cobalt-nickel oxide(CoNiO_(x)).Essentially,the p-n homojunction configuration with facile p-doping engineering improves carrier separation efficiency and facilitates carrier transfer to the nanowire surface,while CoNiO_(x)decoration further boosts PEC reaction activity and carrier dynamics at the nanowire/electrolyte ***,the constructed photosensor achieves a high responsivity of 247.8 mA W^(-1)while simultaneously exhibiting excellent operating ***,based on the remarkable stability and high responsivity of the device,a glucose sensing system was established with a demonstration of glucose level determination in real human *** work offers a feasible and universal approach in the pursuit of high-performance bio-related sensing applications via a rational design of PEC devices in the form of nanostructured architecture with strategic doping engineering.

关键词： p-n GaN nanowires Strategic p-doping Surface decoration Photoelectrochemical sensor Glucose sensing

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Three-Dimensional Spatial-Temporal Near-Field Passive Localization Based on an Exact Spatial Propagation Model

Three-Dimensional Spatial-Temporal Near-Field Passive Locali...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jiaxiong Fang Juan Liu Hua Chen Wei Liu Ye Tian Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China School of Electronic Engineering and Computer Science Queen Mary University of London London UK

Based on the exact source-sensor spatial geometry, a three-dimensional (3-D) spatial-temporal localization algorithm for multiple near-field (NF) sources is proposed without adopting the Fresnel approximation, which simplifies the spatial phase difference by Taylors polynomial. In addition, considering the propagation attenuation which varies from different sensors, the spatial and temporal information can be exploited to construct a third-order parallel factor (PARAFAC) data model and the array manifold matrices can be extracted by trilinear decomposition; then, estimation of the unambiguous range and angle parameters of the NF sources is achieved from the spatial amplitude-phase factors by the least squares method. The obtained 3-D parameters associated with each source require no additional pairing process, as also demonstrated by simulation results.

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Near-eye light field display based on biological stereoscopic vision

Near-eye light field display based on biological stereoscopi...

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The 2023 International Conference on Display Technology, (ICDT 2023)

作者： Zhao, Jian Xia, Jun Xu, Yue Jiang, Yujin School of Computer Engineering Nanjing Institute of technology No.1 Hongjing Road Jiangsu Nanjing211167 China Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and Engineering Southeast University Nanjing210018 China SuXin Vision Technologies Co Ltd No.2888 Dongwu Road Jiangsu Suzhou215000 China

Near-eye display technology can provide users with an immersive visual experience. However, there are still many challenges in this technology, the most urgent of which is visual comfort. The main reason is that the display device cannot render the correct depth cues to solve the conflict between the human eye's radial angle and adjustment, resulting in dizziness, nausea, binocular fatigue and other problems for users to use for a long time. In this paper, we will analyze and review the technical schemes which can provide accurate or near-accurate depth clues in the current near-eye display technology. © 2023, John Wiley and Sons Inc. All rights reserved.

关键词： Stereo image processing

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FEMD: Feature Enhancement-aided Multimodal Feature Fusion Approach for Smart Contract Vulnerability Detection

FEMD: Feature Enhancement-aided Multimodal Feature Fusion Ap...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Juan Li Rui Li Youshui Lu Bowen Cai Yulin Cao Hang Lin Xingxing Li Chan Li School of Computer Science Qinghai Normal University Xining China School of Computer Science and Technology Xidian University The State Key Laboratory of Tibetan Intelligent Information Processing and Application School of Computer Science Qinghai Normal University Xian China School of the Instrument Science and Technology and School of Electrical Engineering Xi’an Jiaotong University Xian China School of Science and Engineering University of Minnesota - Twin City Minneapolis USA

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Smart contracts, due to their immutability and transparency upon deployment, entail significant economic and systemic risks from any vulnerabilities present. Traditional vulnerability detection methods suffer from low automation and high false positive rates, while existing deep learning-based approaches inadequately extract contract features, thereby limiting detection accuracy. To address these issues, this paper proposes FEMD: a feature-enhanced aided multimodal feature fusion method for smart contract vulnerability detection. Building on the foundation of addressing the low automation of traditional detection tools, our method improves the model’s feature extraction performance and detection capabilities. Specifically, we construct a contract graph through Comprehensive Expert-Graph Fusion, combining multi-modal feature fusion using a multi-head attention mechanism with expert patterns to ensure the capture and effective preservation of all critical information during the fusion process. To delve deeper into potential information within smart contract graphs, we employ a Feature Enhancer that leverages transpose operations on feature matrices to extract complex interaction patterns across different dimensions. Our approach is validated through batches of experiments on the Ethereum open dataset focusing on reentrancy and timestamp dependency vulnerabilities, demonstrating significant improvements in detection accuracy and robustness.

关键词： Economics Automation Accuracy Limiting Smart contracts Buildings Focusing Feature extraction Robustness Data mining

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Ghost-in-Wave: How Speaker-Irrelative Features Interfere DeepFake Voice Detectors

Ghost-in-Wave: How Speaker-Irrelative Features Interfere Dee...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xuan Hai Xin Liu Zhaorun Chen Yuan Tan Song Li Weina Niu Gang Liu Rui Zhou Qingguo Zhou School of Information Science and Engineering Lanzhou University Lanzhou China Elmore Family School of Electrical and Computer Engineering Purdue University IN USA The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Recent speech synthesis technology can generate high-quality speech indistinguishable from human speech, thus introducing various security and privacy risks. Numerous recent studies have focused on fake voice detection to address these risks, with many claiming to achieve ideal performance. However, is this really the case? A recent research work introduced Speaker-Irrelative-Features (SiFs), unrelated to the information in speech files but capable of influencing fake detectors. This means that existing detectors may rely on SiFs to a certain extent to distinguish real and fake speech. In this paper, we introduce an evaluation framework to evaluate the influence of SiFs in existing fake voice detectors in depth. We evaluate three SiFs which include background noise, the mute parts before and after voice, and the sampling rate on ASVspoof2019 and FoR. Our results confirm the substantial influence of SiFs on fake voice detection performance, and we delve into the analysis of the underlying mechanisms.

关键词： Privacy Deepfakes Detectors Feature extraction Background noise Speech synthesis Security

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High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing

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Light(science & Applications) 2025年第1期14卷 227-237页

作者： Xiangyan Meng Nuannuan Shi Guojie Zhang Junshen Li Ye Jin Shiyou Sun Yichen Shen Wei Li Ninghua Zhu Ming Li Key Laboratory of Optoelectronic Materials and Devices Institute of SemiconductorsChinese Academy of SciencesBeijing100083China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of SciencesBeijing100049China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing100049China China Academy of Space Technology(Xi’an) Xi’anShaanxi710100China WeChat Pay Lab 33 Shenzhen Tencent Computer System Co.Ltd.Shenzhen518054China Lightelligence Group Hangzhou311121China

The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing *** from the available optical multidimensional information entropy,optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical *** limitations,in terms of device size and photonic integration scale,have hindered the performance of optical ***,an ultrahigh computing density optical tensor processing unit(OTPU),which is grounded in an individual microring resonator(MRR),is introduced to respond to these *** the independent tuning of multiwavelength lasers,the operational capabilities of an MRR are orchestrated,culminating in the formation of an optical tensor *** design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time,wavelength,and frequency of *** experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/***,the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%.These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.

关键词： tuning resonator tensor

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A Dual-Band MIMO Monopole Antenna with Enhanced Isolation for Sub 6 GHz 5G Applications

A Dual-Band MIMO Monopole Antenna with Enhanced Isolation fo...

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2024 International Conference on Advances in electrical and Communication Technologies, ICAECOT 2024

作者： Hamrioui, Fatma Zohra Bouaza, Abdelmaoula Touhami, Rachida Yagoub, Mustapha C.E. Azrar, Arab Electronic Department 10 Rue des Frères OUDEK El Harrach Algiers16200 Algeria Usthb university Bp32 Instrumentation laboratory Electronics and Informatics faculty El Alia Bab Ezzouar Algiers Algeria University of Ottawa Element laboratory School of Electrical Engineering and Computer Science Ottawa Canada Institute of Electrical and Electronic Engineering University M'Hamed BOUGARA-Boumerdes Signals and Systems Laboratory Electronics Department Boumerdes Algeria

ISBN: (纸本)9798350353754

In this paper, a novel dual-band MIMO monopole antenna for 5G applications is presented. The proposed MIMO antenna is made up of two rings that are T-shaped, generating two distinguished bands: the N77 band and the 6 GHz 5G band. A Tshaped ground branch with a bottom slit is integrated into the ground plane to mitigate the mutual coupling at lower and higher operating bands by redistributing the current, thus improving the isolation enhancement. A reversed T-shaped grounded parasitic element with extra grounded parasitic elements on the partial ground is inserted on top of the substrate, between the MIMO elements. The grounded process is introduced by inserting two metallic vias in each branch of the parasitic element. These parasitic elements effectively reduce the coupling between the MIMO antennas by restricting the current to the respective antenna, thus improving the isolation at the higher band. To verify the design principle of the suggested MIMO antenna, this latter is manufactured and tested. It exhibits excellent impedance matching and high isolation characteristics, and a compact footprint of 29 mm × 42.5 mm. Thus, it is attractive for 5G MIMO systems. © 2024 IEEE.

关键词： Monopole antennas

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