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Towards silicon photonic neural networks for artificial intelligence

science China(Information sciences) 2020年第6期63卷 105-118页

作者： Bowen BAI Haowen SHU Xingjun WANG Weiwen ZOU State Key Laboratory of Advanced Optical Communications System and Networks School of Electronics Engineering and Computer Science Peking University Frontiers Science Center for Nano-optoelectronics Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(iMLic) Department of Electronic Engineering Shanghai Jiao Tong University

Brain-inspired photonic neural networks for artificial intelligence have attracted renewed interest. For many computational tasks, such as image recognition, speech processing and deep learning, photonic neural networks have the potential to increase the computing speed and energy efficiency on the orders of magnitude compared with digital electronics. Silicon Photonics, which combines the advantages of electronics and photonics, brings hope for the large-scale photonic neural network integration. This paper walks through the basic concept of artificial neural networks and focuses on the key devices which construct the silicon photonic neuromorphic systems. We review some recent important progress in silicon photonic neural networks, which include multilayer artificial neural networks and brain-like neuromorphic systems, for artificial intelligence. A prototype of silicon photonic artificial intelligence processor for ultra-fast neural network computing is also proposed. We hope this paper gives a detailed overview and a deeper understanding of this emerging field.

关键词： photonic neural networks artificial intelligence deep learning photonic computing accelerator silicon photonics

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A Horizontal Federated Learning Approach to IoT Malware Traffic Detection: An Empirical Evaluation with N-BaIoT Dataset 26

A Horizontal Federated Learning Approach to IoT Malware Traf...

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26th International Conference on Advanced communications Technology, ICACT 2024

作者： Do, Phuc Hao Le, Tran Duc Vishnevsky, Vladimir Berezkin, Aleksandr Kirichek, Ruslan The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Saint-Petersburg Russia Danang Architecture University Da Nang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia University of Science and Technology The University of Danang Da Nang Viet Nam The University of Danang University of Science and Technology Information Technology Faculty Danang Viet Nam V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia Institute of Control Sciences of Russian Academy of Sciences Russia Bonch Bruevich Saint Petersburg State University of Telecommunications Department of Programming Engineering and Computer Science Russia

ISBN: (纸本)9791188428120

The increasing prevalence of botnet attacks in IoT networks has led to the development of deep learning techniques for their detection. However, conventional centralized deep learning models pose challenges in simultaneously ensuring user data privacy and detecting botnet attacks. To address this issue, this study evaluates the efficacy of Federated Learning (FL) in detecting IoT malware traffic while preserving user privacy. The study employs N-BaIoT, a dataset of real-world IoT network traffic infected by malware, and compares the effectiveness of FL models using Convolutional Neural Network, Long Short-Term Memory, and Gated Recurrent Unit models with a centralized approach. The results indicate that FL can achieve high performance in detecting abnormal traffic in IoT networks, with the CNN model yielding the best results among the three models evaluated. The study recommends the use of FL for IoT malware traffic detection due to its ability to preserve data privacy. © 2024 Global IT Research Institute - GIRI.

关键词： Malware

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Simplification of Edge Network Architecture with Open Packet Switches and Pluggable Transceivers

Simplification of Edge Network Architecture with Open Packet...

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LEOS Summer Topical Meetings

作者： Julie Raulin Jim Zou Scott Hill John Griffiths Gawen Davey Alexander Jeffries Ian Cooper Paul Gunning Cormac J. Sreenan Fatima C. Garcia Gunning Tyndall National Institute Ireland School of Computer Science and Information Technology University College Cork Ireland Adtran Networks SE Martinsried/Munich Germany Keysight Technologies Wokingham Berkshire UK APS Networks B.V. Den Haag The Netherlands BT Research and Network Strategy (RaNS) Ipswich UK Broadband Communication Group Lund University Lund Sweden

This paper reports and demonstrates a packetponder for access/metro node consolidation and aggregation using common-form-factor pluggables (CFFP), which can simplify edg e network architectures.

ISBN: (数字)9798350393873

ISBN: (纸本)9798350393880

This paper reports and demonstrates a packetponder for access/metro node consolidation and aggregation using common-form-factor pluggables (CFFP), which can simplify edg e network architectures.

关键词： Network architecture Routing Transceivers Chemical elements Carbon footprint Photonics

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Classification of Colorectal Cancer using ResNet and EfficientNet Models

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Open Biomedical Engineering Journal 2024年 18卷

作者： Abhishek Ranjan, Abhishek Srivastva, Priyanshu Prabadevi, B. Rajagopal, Sivakumar Soangra, Rahul Subramaniam, Shamala K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Sensor and Biomedical Technology Vellore Institute of Technology Crean College of Health and Behavioral Sciences Chapman University Department of Communication Technology and Networks Universiti Putra Malaysia

Introduction: Cancer is one of the most prevalent diseases from children to elderly adults. This will be deadly if not detected at an earlier stage of the cancerous cell formation, thereby increasing the mortality rate. One such cancer is colorectal cancer, caused due to abnormal growth in the rectum or colon. Early screening of colorectal cancer helps to identify these abnormal growth and can exterminate them before they turn into cancerous cells. Aim: Therefore, this study aims to develop a robust and efficient classification system for colorectal cancer through Convolutional Neural networks (CNNs) on histological images. Methods: Despite challenges in optimizing model architectures, the improved CNN models like ResNet34 and EfficientNet34 could enhance Colorectal Cancer classification accuracy and efficiency, aiding doctors in early detection and diagnosis, ultimately leading to better patient outcomes. Results: ResNet34 outperforms the EfficientNet34. Conclusion: The results are compared with other models in the literature, and ResNet34 outperforms all the other models. © 2024 The Author(s).

关键词： CNN Colorectal cancer Deep learning EfficientNetB4 Histology Learning rate Loss function Optimizer ResNet34 ROC curve Transforms

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An iterative algorithm for artifacts removal in Fourier-domain optical coherence tomography 25

An iterative algorithm for artifacts removal in Fourier-doma...

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Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXV 2021

作者： Wang, Mengyuan Ling, Yuye Shao, Shuo Su, Yikai John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai China Department of Electronic Engineering State Key Lab of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9781510640962

ISBN: (纸本)9781510640955

FD-OCT is a widely used technology which could provide high-resolution 3D reconstruction images. Conventional OCT uses IDFT reconstruction method, which could obtain an FFT-limited axial resolution. Recently, several optimization-based methods have reportedly achieved a resolution improvement, while undesired noise artifacts might appear in their result, which could degrade the image quality. In this work, we proposed an iterative error reduction method in order to remove the artifacts as well as improve the resolution. A numerical simulation is designed to validate our algorithm. Two reconstruction methods including IDFT reconstruction, and l1 minimization are selected for a comparative study. Specifically, we conduct the simulation at four different noise levels. The result shows that our proposed method could greatly suppress the artifact and obtain a great reconstruction even when the SNR is reduced. © 2021 SPIE.

关键词： Image reconstruction

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Fully integrated hybrid microwave photonic receiver

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Photonics Research 2022年第6期10卷 1472-1483页

作者： JIACHEN LI SIGANG YANG HONGWEI CHEN XINGJUN WANG MINGHUA CHEN WEIWEN ZOU Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Microwave photonic receivers are a promising candidate in breaking the bandwidth limitation of traditional radio-frequency(RF)*** further balance the performance superiority with the requirements regarding size,weight,and power consumption(SWa P),the implementation of integrated microwave photonic microsystems has been considered an upgrade ***,up to now,to the best of our knowledge,chip-scale fully integrated microwave photonic receivers have not been reported due to the limitation of material *** this paper,we report a fully integrated hybrid microwave photonic receiver(FIH-MWPR)obtained by comprising the indium phosphide(In P)laser chip and the monolithic silicon-on-insulator(SOI)photonic circuit into the same substrate based on the low-coupling-loss micro-optics *** from the integration of all optoelectronic components,the packaged FIH-MWPR exhibits a compact volume of 6 cmand low power consumption of 1.2 *** FIH-MWPR supports a wide operation bandwidth from 2 to 18 ***,its RF-link performance to down-convert the RF signals to the intermediate frequency is experimentally characterized by measuring the link gain,the noise figure,and the spurious-free dynamic range metrics across the whole operation frequency ***,we have utilized it as a de-chirp receiver to process the broadband linear frequencymodulated(LFM)radar echo signals at different frequency bands(S-,C-,X-,and Ku-bands)and successfully demonstrated its high-resolution-ranging *** the best of our knowledge,this is the first realization of a chip-scale broadband fully integrated microwave photonic receiver,which is expected to be an important step in demonstrating the feasibility of all-integrated microwave photonic microsystems oriented to miniaturized application scenarios.

关键词： method microwave bands

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Wavelength-Division-Multiplexed Transmission and Dispersion Compensation Enabled by Soliton Microcombs and Cascaded Microrings

Wavelength-Division-Multiplexed Transmission and Dispersion ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yuanbin Liu Hongyi Zhang Jiacheng Liu Liangjun Lu Jiangbing Du Yu Li Zuyuan He Jianping Chen Linjie Zhou Andrew W. Poon Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Shanghai Jiao Tong University Shanghai China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu China Department of Electronic and Computer Engineering Photonic Device Laboratory The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

We demonstrate wavelength-division-multiplexed data transmission and dispersion compensation of 25 Gb/s $\times 9$ on-off-keying signals over a 20-km singlemode fiber using an integrated single-soliton microcomb and... 详细信息

ISBN: (纸本)9798350369311

关键词： Solitons Lasers and electrooptics Wavelength division multiplexing Data communication Quantum cascade lasers Electro-optical waveguides Optical fiber dispersion Fiber lasers

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Who benefits from altmetrics? The effect of team gender composition on the link between online visibility and citation impact

arXiv

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arXiv 2023年

作者： Vásárhelyi, Orsolya Horvát, Emoke-Ágnes Laboratory for Networks Technology and Innovation Centre for Advanced Studies Corvinus University Budapest Hungary Department of Communication Studies School of Communication Northwestern University EvanstonIL United States Department of Computer Science McCormick School of Engineering Northwestern University EvanstonIL United States EvanstonIL United States

Online science dissemination has quickly become crucial in promoting scholars' work. Recent literature has demonstrated a lack of visibility for women's research, where women's articles receive fewer academic citations than men's. The informetric and scientometric community has briefly examined gender-based inequalities in online visibility. However, the link between online sharing of scientific work and citation impact for teams with different gender compositions remains understudied. Here we explore whether online visibility is helping women overcome the gender-based citation penalty. Our analyses cover the three broad research areas of computer science, Engineering, and Social sciences, which have different gender representation, adoption of online science dissemination practices, and citation culture. We create a quasi-experimental setting by applying Coarsened Exact Matching, which enables us to isolate the effects of team gender composition and online visibility on the number of citations. We find that online visibility positively affects citations across research areas, while team gender composition interacts differently with visibility in these research areas. Our results provide essential insights into gendered citation patterns and online visibility, inviting informed discussions about decreasing the citation gap. © 2023, CC0.

关键词： Visibility

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An ns-3 model for multipath communication with terrestrial and satellite links 1

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20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems, MMB 2020

作者： Deutschmann, Jörg Hielscher, Kai-Steffen Jens German, Reinhard Department of Computer Science 7 Computer Networks and Communication Systems University of Erlangen-Nürnberg Martensstraße 3 Erlangen91058 Germany

ISBN: (数字)9783030430245

ISBN: (纸本)9783030430238

Some terrestrial Internet access links provide only low data rates. Internet access via geostationary satellites on the other hand provides data rates of up to 50 Mbit/s, but suffers from high latencies. The combination of low data rate, low latency Internet access (e.g., DSL light) and high data rate, high latency Internet access (e.g., geostationary satellites) can utilize the advantages of both. We discuss multipath communication architectures and scheduling strategies for such heterogeneous link combinations. The solution described in this paper relies on Split TCP and Performance Enhancement Proxies. We implement and evaluate the solution with the network simulator ns-3. A well-established traffic model for loading websites is enhanced with different HTTP variants. The results show that the combination of heterogeneous link types can result in page load times close to as if there was a high data rate, low latency Internet access. © Springer Nature Switzerland AG 2020.

关键词： Geostationary satellites

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Design of a hybrid genetic algorithm for time-sensitive networking 1

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20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems, MMB 2020

作者： Arestova, Anna Hielscher, Kai-Steffen Jens German, Reinhard Department of Computer Science 7 Computer Networks and Communication Systems University of Erlangen-Nürnberg Martensstraße 3 Erlangen91058 Germany

ISBN: (数字)9783030430245

ISBN: (纸本)9783030430238

With Time-Sensitive Networking (TSN), the IEEE 802.1 Task Group is extending the Ethernet standard by time-sensitive capabilities to establish a common ground for real-time communication systems via Ethernet. The Time-Sensitive Networking Task Group introduces a time-triggered transmission approach in IEEE 802.1Qbv to enable a deterministic transmission of time-critical network traffic, which requires scheduling strategies. Genetic algorithms are qualified to solve these scheduling problems in Time-Sensitive networks. The difficulty is to design the genetic algorithm to find an optimal or a near-optimal solution for different complex problems taking performance and quality of the schedule into account. The complexity of schedules for TSN depends on the decision space of a network designer comprising the possibility to combine a variable number of network participants, a variable number of TSN flows, as well as assuming fixed or flexible routes for the flows. In this paper, we discuss a design approach for a hybrid genetic algorithm including chromosome representation for the routing and scheduling problems in TSN, the choice of genetic operators, and a neighborhood search to find a near-optimal solution. Additionally, we introduce an approach to compress the resulting schedules. Our evaluations show that the proposed hybrid genetic algorithm is able to compete with the well-adapted NEH algorithm in terms of schedule quality, and it outperforms the NEH algorithm regarding the computing time. © Springer Nature Switzerland AG 2020.

关键词： Genetic algorithms

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