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Improve Chinese Aspect Sentiment Quadruplet Prediction via Instruction Learning Based on Large Generate Models

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Computers, Materials & Continua 2024年第3期78卷 3391-3412页

作者： Zhaoliang Wu Yuewei Wu Xiaoli Feng Jiajun Zou Fulian Yin College of Information and communication engineering Communication University of ChinaBeijing100024China The State Key Laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China department of Electronic engineering Tsinghua UniversityBeijing100084China

Aspect-Based Sentiment Analysis(ABSA)is a fundamental area of research in Natural Language Processing(NLP).Within ABSA,Aspect Sentiment Quad Prediction(ASQP)aims to accurately identify sentiment quadruplets in target sentences,including aspect terms,aspect categories,corresponding opinion terms,and sentiment ***,most existing research has focused on English ***,while ASQP has seen significant progress in English,the Chinese ASQP task has remained relatively *** inspiration from methods applied to English ASQP,we propose Chinese generation templates and employ prompt-based instruction learning to enhance the model’s understanding of the task,ultimately improving ASQP performance in the Chinese ***,under the same pre-training model configuration,our approach achieved a 5.79%improvement in the F1 score compared to the previously leading ***,when utilizing a larger model with reduced training parameters,the F1 score demonstrated an 8.14%***,we suggest a novel evaluation metric based on the characteristics of generative models,better-reflecting model *** results validate the effectiveness of our approach.

关键词： ABSA ASQP LLMs sentiment analysis Chinese comments

A Generalized Array Factor for Time-Modulated Hexagonal Based Antenna Array Geometry With Novel Trapezoidal Switching

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1967-1972页

作者： Gopi Ram department of Electronics and communication engineering National Institute of TechnologyWarangal 506004India

The concept of the time-modulated array has been emerging as an alternative to the complex phase shifters,which lowers the cost of the array feeding network due to the utilization of radio frequency(RF)*** various forms of hexagonal antenna array geometries can be used for applications like surveillance tracking in phased array radar and wireless communication *** work proposes the generalized array factor(AF)for the hexagonal antenna array geometry based on time *** time modulation in generalized hexagonal geometry can maintain the fixed static amplitude excitation,giving more flexibility over ***,a novel trapezoidal switching function is also proposed and applied to the generalized array factor to enable future researchers to use this array factor in the field of advancement to observe how switching schemes like trapezoidal and rectangular affect the array pattern's side lobe level(SLL).The generalized equation can be utilized for the analysis and synthesis of radiation characteristics of the time-modulated hexagonal array(TMHA),time-modulated concentric hexagonal array(TMCHA),time-modulated hexagonal cylindrical array(TMHCA),and time-modulated hexagonal concentric cylindrical array(TMHCCA).The numerical result illustrates the generation of AF of time-modulated hexagonal structures and also shows that the trapezoidal switching sequence outperforms the rectangular switch using the cat swarm optimization(CSO)approach.

关键词： Hexagonal array geometry radiation pattern time-modulation trapezoidal pulse

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Impact of dark current on pinned photo-diode capacitance of CMOS image sensor in low illumination regime

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Optoelectronics Letters 2024年第11期20卷 654-657页

作者： Mohsin Suharwerdi Gausia Qazi department of Electronics & communication engineering National Institute of Technology

Applications for quanta and space sensing both depend on efficient low-light imaging. To precisely optimize and design image sensor pixels for these applications, it is crucial to analyze the mechanisms behind dark cu... 详细信息

关键词： A

Graph Signal Reconstruction from Low-Resolution Multi-Bit Observations

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Chinese Journal of Electronics 2024年第1期33卷 153-160页

作者： Zhaoting LIU Chen YU Yafeng WANG Shuchen LIU School of communication engineering Hangzhou Dianzi University

Low hardware cost and power consumption in information transmission, processing and storage is an urgent demand for many big data problems, in which the high-dimensional data often be modelled as graph *** paper considers the problem of recovering a smooth graph signal by using its low-resolution multi-bit quantized observations. The underlying problem is formulated as a regularized maximum-likelihood optimization and is solved via an expectation maximization scheme. With this scheme, the multi-bit graph signal recovery(MB-GSR) is efficiently implemented by using the quantized observations collected from random subsets of graph nodes. The simulation results show that increasing the sampling resolution to 2 or 3 bits per sample leads to a considerable performance improvement, while the energy consumption and implementation costs remain much lower compared to the implementation of high resolution sampling.

关键词： Quantization (signal) Costs Power demand Simulation Energy resolution Signal sampling Signal reconstruction

Low-Complexity Reconstruction of Covariance Matrix in Hybrid Uniform Circular Array

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China communications 2024年第3期21卷 66-74页

作者： Fu Zihao Liu Yinsheng Duan Hongtao Information School Communication University of ChinaBeijing 100024China Beijing Institute of Electronic System engineering Beijing 100854China School of Electronic and Information engineering Beijing Jiaotong UniversityBeijing 100044China Beijing radio Monitoring Station of State radio Monitoring Center(SRMC) Beijing 100037China

Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency *** this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm(BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array(UCA)will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.

关键词： hybrid array millimeter-wave spatial covariance matrix uniform circular array

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Joint Rain Streaks & Haze Removal Network for Object Detection

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Computers, Materials & Continua 2024年第6期79卷 4683-4702页

作者： Ragini Thatikonda Prakash Kodali Ramalingaswamy Cheruku Eswaramoorthy K.V department of Electronics and communication engineering National Institute of TechnologyWarangal506004India department of Computer Science and engineering National Institute of TechnologyWarangal506004India department of Electronics and communication engineering Indian Institute of Information TechnologyDesign and ManufacturingKurnool518008India

In the realm of low-level vision tasks,such as image deraining and dehazing,restoring images distorted by adverse weather conditions remains a significant *** emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks(CNNs),supplanting traditional methods reliant on prior ***,the evolution of CNN architectures has tended towards increasing complexity,utilizing intricate structures to enhance performance,often at the expense of computational *** response,we propose the Selective Kernel Dense Residual M-shaped Network(SKDRMNet),a flexible solution adept at balancing computational efficiency with network accuracy.A key innovation is the incorporation of an M-shaped hierarchical structure,derived from the U-Net framework as M-Network(M-Net),within which the Selective Kernel Dense Residual Module(SDRM)is introduced to reinforce multi-scale semantic feature *** methodology employs two sampling techniques-bilinear and pixel unshuffled and utilizes a multi-scale feature fusion approach to distil more robust spatial feature map *** the reconstruction phase,feature maps of varying resolutions are seamlessly integrated,and the extracted features are effectively merged using the Selective Kernel Fusion Module(SKFM).Empirical results demonstrate the comprehensive superiority of SKDRMNet across both synthetic and real rain and haze datasets.

关键词： Image deraining Selective Dense Residual Module(SDRM) Selective Kernel Fusion Module(SKFM) Selective KernelDense Residual M-Shaped Network(SKDRMNet)

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

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Computers, Materials & Continua 2024年第8期80卷 2099-2119页

作者： Tajmal Hussain Jungpyo Hong Jongwon Seok department of Information and communication engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational *** technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing *** this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing ***,features are extracted by the VGG19 convolutional ***,after processing through the GAP layer,the extracted features are fed to the SVM classifier for *** this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the *** outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS ***,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

关键词： Smart manufacturing steel defect detection deep learning CNN

Performance Improvement of Multiband Triangular Microstrip Patch Antenna Using Frequency Selective Surface

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 316-321页

作者： MAHENDRAN Krishnakumar GAYATHRI Rajaraman department of Electronics and communication engineering Annamalai UniversityChidambaram 608002India

Today's antennas have to operate in multiple resonant frequencies to satisfy the need of recent advances in communication *** paper presents split ring resonator based triangular multiband antenna whose antenna performance is enhanced with the help of frequency selective surfaces(FSSs).The antenna has multiple resonances at S,C,and X *** array of 4×3 crisscross-shaped unit cells are arranged to form the FSS *** antenna is fed with a microstrip line feeding *** proposed antenna operates at 3.5 GHz,4.1 GHz,5.5GHz,9.4GHz,and 9.8 GHz with a better return loss and *** and measured results yield a good match.

关键词： triangular microstrip antenna split ring resonator frequency selective surface(FSS) metamaterial

A nano-plasmonic HMIM waveguide based concurrent dual-band BPF using circular ring resonator

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Optoelectronics Letters 2024年第3期20卷 152-156页

作者： Miriyala Sridhar Surendra Kumar Bitra TS N Murthy Koppireddi Padmaraju department of Electronics and communication engineering Koneru Lakshmaiah Education FoundationGunturIndia Astra Microwave Products Ltd. HyderabadIndia department of Electronics and communication engineering JNTU-GV College of EngineeringVizianagaramIndia department of Electronics and communication engineering Jawaharlal Nehru Technological University KakinadaKakinadaIndia

This article analyzes the transmission line characteristics of plasmonic hybrid metal insulator metal(HMIM) wave-guide, circular ring resonator(CRR) based dual-band band-pass filters with two transmission poles in both pass-bands in the optical regime using coupled line feed. The transmission line characteristics of an HMIM waveguide, such as characteristic impedance(Z_(PV)), effective refractive index(n_(eff)) and propagation length(L_(spp)), have been obtained by using full wave simulation.

关键词： waveguide resonator circular

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