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International Conference on Integrated Circuits and Microsystems (ICICM)

作者： Bin Wang Pengcheng Huang Huiqing You Yaohua Wang Key Laboratory of Advanced Microprocessor Chips and Systems Changsha China College of Computer Science National University of Defense Technology Changsha China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China

As the level of circuit integration increases, the physical design becomes more and more complex, iterative static timing analysis(STA) is one of the most time-consuming task to achieve timing closure. After the route stage, fast and accurate timing analysis prediction can effectively reduce the number of static timing analysis in iterations, thereby improving design efficiency and reducing design cycle. In order to quickly predict the timing results after route, we propose a fast timing analysis predictor based on gate recurrent unit (GRU) neural network. This method extracts the features of combinations of cells and nets, assigns attention weights to different combinations, then predicts the hold slacks and setup slacks of each path in multi-corners. The experimental results in the sub-30nm show that the standard deviation of the prediction error ranges 5.41∼16.44ps, and the mean absolute error ranges 6.87∼18.55ps, and the prediction correlation is more than 0.96. Moreover, the speed of timing path prediction is more than 197 times faster than the analysis by STA tools, so that it can effectively and accurately accelerate the process of timing analysis and improve the efficiency of physical design.

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Submilliwatt, widely tunable coherent microcomb generation with feedback-free operation

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advanced Photonics 2023年第3期5卷 144-154页

作者： Haowen Shu Lin Chang Chenghao Lao Bitao Shen Weiqiang Xie Xuguang Zhang Ming Jin Yuansheng Tao Ruixuan Chen Zihan Tao Huajin Chang Shaohua Yu Qifan Yang Xingjun Wang John E.Bowers Peking University School of ElectronicsState Key Laboratory of Advanced Optical Communication Systems and NetworksBeijingChina University of California Santa BarbaraDepartment of Electrical and Computer EngineeringSanta BarbaraCaliforniaUnited States Peking University School of PhysicsState Key Laboratory for Artificial Microstructure and Mesoscopic PhysicsBeijingChina Peng Cheng Laboratory ShenzhenChina Peking University Frontiers Science Center for Nano-OptoelectronicsBeijingChina

Microcombs are revolutionizing optoelectronics by providing parallel, mutually coherent wavelengthchannels for time-frequency metrology and information processing. To implement this essential function inintegrated photonic systems, it is desirable to drive microcombs directly with an on-chip laser in a simpleand flexible way. However, two major difficulties have prevented this goal: (1) generating mode-lockedcomb states usually requires a significant amount of pump power and (2) the requirement to align laser andresonator frequency significantly complicates operation and limits the tunability of the comb lines. Here, weaddress these problems by using microresonators on an AlGaAs on-insulator platform to generate dark-pulsemicrocombs. This highly nonlinear platform dramatically relaxes fabrication requirements and leads to arecord-low pump power of <1 mW for coherent comb generation. Dark-pulse microcombs facilitated bythermally controlled avoided mode crossings are accessed by direct distributed feedback laser *** any feedback or control circuitries, the comb shows good coherence and stability. With around150 mW on-chip power, this approach also leads to an unprecedentedly wide tuning range of over one freespectral range (97.5 GHz). Our work provides a route to realize power-efficient, simple, and reconfigurablemicrocombs that can be seamlessly integrated with a wide range of photonic systems.

关键词： dark-pulse microcomb direct pumping scheme widely tunable source

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A 0.9–1.4-GHz Q-Enhanced CMOS Tunable Bandpass Filter With Constant Fractional Bandwidth and Two Transmission Zeros

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IEEE Microwave and Wireless Technology Letters 2023年第6期33卷 667-670页

作者： Kun Li Xiang Li Shuangyang Wu Pei-Ling Chi Tao Yang School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Research Center of Advanced RF Chips and Systems Nanhu Laboratory Jiaxing China Department of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan

A tunable differential $Q$ -enhanced bandpass filter covering 0.9–1.4 GHz with constant fractional bandwidth (FBW) is proposed using 40-nm CMOS technology in this letter. The proposed filter is constructed by two resonators which consist of ON-chip integrated inductors and varactors. The inductors of the two resonators are placed close to each other to form the mainline magnetic coupling of the filter. Besides the mainline coupling, the source port and load port are connected directly by capacitors, forming the source-to-load coupling. With the proposed structure, two transmission zeros (TZs) can be obtained, which can greatly increase the stopband rejection. Meanwhile, nMOS cross-coupled pairs are used as the $Q$ -enhanced cells to reduce the insertion loss (IL) and further improve the filter selectivity. A filter prototype based on 40-nm CMOS process is fabricated to validate the proposed structure. The center frequency (CF) of the proposed filter can be tuned from 0.9 to 1.4 GHz while keeping the FBW constant at 8%.

关键词： Resonator filters Band-pass filters Microwave filters Filtering theory Couplings Equivalent circuits Magnetic separation

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A Material Identification Approach Based on Wi-Fi Signal

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computers, Materials & Continua 2021年第12期69卷 3383-3397页

作者： Chao Li Fan Li Wei Du Lihua Yin Bin Wang Chonghua Wang Tianjie Luo Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510700China PCL Research Center of Cyberspace Security Peng Cheng LaboratoryShenzhen518052China Department of Computer Science and Computer Engineering University of ArkansasFayetteville72701USA College of Electrical Engineering Zhejiang UniversityHangzhou310058China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Material identification is a technology that can help to identify the type of target *** approaches depend on expensive instruments,complicated pre-treatments and professional *** is difficult to find a substantial yet effective material identification method to meet the daily use *** this paper,we introduce a Wi-Fi-signal based material identification approach by measuring the amplitude ratio and phase difference as the key features in the material classifier,which can significantly reduce the cost and guarantee a high level *** practical measurement of WiFi based material identification,these two features are commonly interrupted by the software/hardware noise of the channel state information(CSI).To eliminate the inherent noise of CSI,we design a denoising method based on the antenna array of the commercial off-the-shelf(COTS)Wi-Fi *** that,the amplitude ratios and phase differences can be more stably utilized to classify the *** implement our system and evaluate its ability to identify materials in indoor *** result shows that our system can identify 10 commonly seen liquids with an average accuracy of 98.8%.It can also identify similar liquids with an overall accuracy higher than 95%,such as various concentrations of salt water.

关键词： Internet of Things Wi-Fi signal channel state information material identification noise elimination

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Extending the Reach of Optical Interconnects with advanced Coded Modulation

Extending the Reach of Optical Interconnects with Advanced C...

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OptoElectronics and Communications Conference, OECC

作者： Yi Lei Xiang Wang Qi Lu Bin Chen School of Computer Science and Information Engineering Hefei University of Technology Hefei China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University China

An advanced coded modulation is proposed based on improved staircase codes using marked bits and geometrically-shaped constellations. Up to 0.95 dB SNR gain and 8.6% reach increase are achieved for beyond 800G data ce...

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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

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computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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Transfer Learning assisted Beam Training via Large-Scale Intelligent Omni-surface in Dynamic Environments

Transfer Learning assisted Beam Training via Large-Scale Int...

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IEEE Conference on Vehicular Technology (VTC)

作者： Zhihan Chen Shuhang Zhang Shuhao Zeng Boya Di School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China

Intelligent omni-directional surfaces (IOS), which can simultaneously reflect and refract incident signals, are considered as a promising solution for enhancing communication quality. To conduct joint beamforming of the BS and IOS, beam training is introduced such that perfect channel state information is not required anymore. However, the propagation environment is usually dynamically varying in practice, leading to frequent beam training procedures and huge training overhead. In this paper, we propose a transfer learning based beam training scheme for the IOS-assisted multi-user system to adapt to the dynamically changing propagation environment. We first build on an offline phase to train a beam prediction model that outputs the optimal beam with the highest data rate given only the received power of a small number of beams as the input. Then a transfer learning based method is developed such that the above beam prediction model can be updated to adapt to the dynamic environment rapidly. Simulation results demonstrate that the proposed scheme outperforms the existing beam training schemes in dynamic environments in terms of the convergence speed and the sum rate.

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How to Design a R-D Model for UAV Video Transmission? 15

How to Design a R-D Model for UAV Video Transmission?

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Yu, Zongyang Yang, Peng Cao, Xianbin Zheng, Dezhi Quek, Tony Q. S. Oliver Wu, Dapeng Beihang University School of Electronic Information Engineering Beijing China Peng Cheng Laboratory Department of Mathematics and Theories Shenzhen China Beijing Institute of Technology Advanced Research Institute of Multidisciplinary Sciences Beijing China Singapore University of Technology and Design Information Systems Technology and Design Singapore City University of Hong Kong Department of Computer Science Kowloon Hong Kong

ISBN: (纸本)9798350324662

Unmanned aerial vehicle (UAV) video transmission has been extensively applied in many crucial fields. However, the problem of designing a rate-distortion (R-D) model for UAV video transmission, which is essential for theoretical analysis of video coding and optimization of video transmission quality, is under-studied. The designed R-D model is desired to be simple, accurate, and generic owing to the limited capability of the UAV. Observing the key role of transformed residuals in the R-D model, this paper elaborately discusses the modeling of the transformed residual distribution and proposes an estimation algorithm to estimate the statistical parameter of the distribution. Specifically, considering the stringent requirements for low complexity and high generalization capability, we first design a linear parameter estimator by mining and analyzing UAV video statistical characteristics. Further, we develop a bias update scheme to improve the accuracy of the estimator. Test results on multiple real video sequences taken by UAVs show that the proposed estimation algorithm is more accurate than benchmarks. © 2023 IEEE.

关键词： expectation maximization algorithm R-D model rate control video coding Video transmission

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Experimental Demonstration of 16D Voronoi Constellation with Two-Level Coding over 50km Four-Core Fiber

arXiv

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arXiv 2024年

作者： Zhao, Can Chen, Bin Cai, Jiaqi Liang, Zhiwei Lei, Yi Xiong, Junjie Ma, Lin Hu, Daohui Sun, Lin Shen, Gangxiang School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Electronic and Information Engineering Soochow University Suzhou China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China

A 16-dimensional Voronoi constellation concatenated with multilevel coding is experimentally demonstrated over a 50 km four-core fiber transmission system. The proposed scheme reduces the required launch power by 6 dB and provides a 17 dB larger operating range than 16QAM with BICM at the outer HD-FEC BER threshold. © 2024, CC BY-NC-SA.

关键词： Digital television

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Partially Occluded Face Expression Recognition with CBAM-Based Residual Network for Teaching Scene

Partially Occluded Face Expression Recognition with CBAM-Bas...

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2023 China Automation Congress, CAC 2023

作者： Bai, Yanxing Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcomes the problem of localized occlusion face feature extraction by focusing on the regions and channels containing important information in the occluded face data through CBAM. Multi-task cascaded convolutional networks (MTCNN) are firstly utilized to localize the key regions of face emotion, and then deep emotion features are extracted by CBAM-ResNet network. The final emotion labels are generated. The effectiveness of this paper's method is verified on the RAF-DB dataset and the occluded CK+ dataset. The experimental accuracy in the RAF-DB dataset is 76.3%, which is 3.74% and 1.64% higher than the accuracy produced by the method of RGBT, and the WLS-RF, respectively. Application experiments are carried out in the real teaching scenario, which verifies the applicability of the algorithm in the real teaching scene. © 2023 IEEE.

关键词： Emotion Recognition

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