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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

Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

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Computers, Materials & Continua 2024年第8期80卷 3107-3122页

作者： Ruijin Xue Shuang Feng Qi Wang School of Computer and Cyber Sciences Communication University of ChinaBeijing100024China State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China

Users’interests are often diverse and multi-grained,with their underlying intents even more *** captur-ing users’interests and uncovering the relationships between diverse interests are key to news ***,diversity is an important metric for evaluating news recommendation algorithms,as users tend to reject excessive homogeneous information in their recommendation ***,recommendation models themselves lack diversity awareness,making it challenging to achieve a good balance between the accuracy and diversity of news *** this paper,we propose a news recommendation algorithm that achieves good performance in both accuracy and *** most existing works that solely optimize accuracy or employ more features to meet diversity,the proposed algorithm leverages the diversity-aware capability of the ***,we introduce an augmented user model to fully capture user intent and the behavioral guidance they might undergo as a ***,we focus on the relationship between the original clicked news and the augmented clicked ***,we propose an effective adversarial training method for diversity(AT4D),which is a pluggable component that can enhance both the accuracy and diversity of news recommendation *** experiments on real-world datasets confirm the efficacy of the proposed algorithm in improving both the accuracy and diversity of news recommendations.

关键词： News recommendation diversity accuracy data augmentation

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

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Computers, Materials & Continua 2024年第5期79卷 2723-2741页

作者： Weijian Fan Ziwei Shi State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China Software Research Institute China United Network Communication Group Co.Ltd.Beijing100024China

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

关键词： Social media false information detection image aesthetic assessment cross-modal consistency

Deep Video Harmonization by Improving Spatial-temporal Consistency

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Machine Intelligence Research 2024年第1期21卷 46-54页

作者： Xiuwen Chen Li Fang Long Ye Qin Zhang Key Laboratory of Media Audio and Video Ministry of Education Communication University of ChinaBeijing 100024China

Video harmonization is an important step in video editing to achieve visual consistency by adjusting foreground appear-ances in both spatial and temporal *** methods always only harmonize on a single scale or ignore the inaccuracy of flow estimation,which leads to limited harmonization *** this work,we propose a novel architecture for video harmoniza-tion by making full use of spatiotemporal features and yield temporally consistent harmonized *** introduce multiscale harmon-ization by using nonlocal similarity on each scale to make the foreground more consistent with the *** also propose a fore-ground temporal aggregator to dynamically aggregate neighboring frames at the feature level to alleviate the effect of inaccurate estim-ated flow and ensure temporal *** experimental results demonstrate the superiority of our method over other state-of-the-art methods in both quantitative and visual comparisons.

关键词： Harmonization temporal consistency video editing video composition nonlocal similarity

A Unified Model Fusing Region of Interest Detection and Super Resolution for Video Compression

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Computers, Materials & Continua 2024年第6期79卷 3955-3975页

作者： Xinkun Tang Feng Ouyang Ying Xu Ligu Zhu Bo Peng School of Computer and Cyber Sciences Communication University of ChinaBeijing100024China Cable Television Technology Research Institute Academy of Broadcasting ScienceBeijing100866China

High-resolution video transmission requires a substantial amount of *** this paper,we present a novel video processing methodology that innovatively integrates region of interest(ROI)identification and super-resolution *** method commences with the accurate detection of ROIs within video sequences,followed by the application of advanced super-resolution techniques to these areas,thereby preserving visual quality while economizing on data *** validate and benchmark our approach,we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical *** proposed model architecture leverages the transformer network framework,guided by a carefully designed multi-task loss function,which facilitates concurrent learning and execution of both ROI identification and resolution enhancement *** unified deep learning model exhibits remarkable performance in achieving super-resolution on our custom *** implications of this research extend to optimizing low-bitrate video streaming *** selectively enhancing the resolution of critical regions in videos,our solution enables high-quality video delivery under constrained bandwidth *** results demonstrate a 15%reduction in transmission bandwidth compared to traditional super-resolution based compression methods,without any perceivable decline in visual *** work thus contributes to the advancement of video compression and enhancement technologies,offering an effective strategy for improving digital media delivery efficiency and user experience,especially in bandwidth-limited *** innovative integration of ROI identification and super-resolution presents promising avenues for future research and development in adaptive and intelligent video communication systems.

关键词： Super resolution region of interest detection video compression

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

Research on Sarcasm Detection Technology Based on Image-Text Fusion

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Computers, Materials & Continua 2024年第6期79卷 5225-5242页

作者： Xiaofang Jin Yuying Yang YinanWu Ying Xu School of Information and Communication Engineering Communication University of ChinaBeijing100024China Cable Television Technology Research Institute Academy of Broadcasting ScienceBeijing100053China

The emergence of new media in various fields has continuously strengthened the social aspect of social *** tend to express emotions in social interactions,and many people even use satire,metaphors,and other techniques to express some negative emotions,it is necessary to detect sarcasm in social comment *** sarcasm,the more reference data modalities used,the better the experimental *** paper conducts research on sarcasm detection technology based on image-text fusion *** effectively utilize the features of each modality,a feature reconstruction output algorithm is *** algorithm is based on the attention mechanism,learns the low-rank features of another modality through cross-modality,the eigenvectors are reconstructed for the corresponding modality through weighted *** only the image modality in the dataset is used,the preprocessed data has outstanding performance in reconstructing the output model,with an accuracy rate of 87.6%.When using only the text modality data in the dataset,the reconstructed output model is optimal,with an accuracy rate of 85.2%.To improve feature fusion between modalities for effective classification,a weight adaptive learning algorithm is *** algorithm uses a neural network combined with an attention mechanism to calculate the attention weight of each modality to achieve weight adaptive learning purposes,with an accuracy rate of 87.9%.Extensive experiments on a benchmark dataset demonstrate the superiority of our proposed model.

关键词： Sentiment analysis sarcasm detection feature fusion feature reconstruction

Energy partition in laser-induced cavitation bubbles near the rigid wall with a gas-containing hole

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Journal of Hydrodynamics 2024年第3期36卷 435-443页

作者： Dong-qiao He Hai-gang Wen Si-yuan Geng Chen-xi Yang Qiang Zhong Zhi-feng Yao College of Water Resources and Civil Engineering China Agricultural UniversityBeijing100083China PowerChina beijing Engineering Corporation Limited Beijing100024China State Key Laboratory of Efficient Utilization of Agricultural Water Resources Beijing100083China beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System China Agricultural UniversityBeijing100083China

To investigate the energy partition in laser-induced cavitation bubbles near the rigid wall with a gas-containing hole,we utilized a nanosecond resolution photography system based on a Q-switched Nd:YAG laser and conventional industrial camera to carefully observe the transient process of bubble collapse near the rigid wall with a gas-containing *** analyzed the generation of collapse microjets and the emission of collapse shock *** found that the cavitation bubble near the rigid wall with a gas-containing hole collapsed at different times and space,and produced various types of shock *** on the far field pressure information of the shock waves measured by hydrophone,the energy of the shock waves generated by the bubble collapse near the rigid wall with a gas-containing hole is calculated for the first *** results show that the ratio of collapse shock wave energy to bubble energy is approximately between 0.7 and 0.8.

关键词： Energy partition bubble collapse laser-induced shock wave gas-containing hole

Dynamic emission characteristics and control strategies of air pollutants from motor vehicles in downtown beijing,China

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Journal of Environmental Sciences 2024年第2期136卷 637-646页

作者： Yan Shen Tongran Wu Aiping Lian Jie Gao Fei Peng Guohua Song Xuefang Wu Yangyang Cui Xinyu Liu Yunfei Wan Jing Yan Yifeng Xue National Engineering Research Center of Urban Environmental Pollution Control Beijing Municipal Research Institute of Eco-Environmental ProtectionBeijing 100037China beijing Municipal Ecology and Environment Bureau Beijing 100048China beijing Jiaotong University Beijing 100091China

This study combined the real-time monitoring and investigation of traffic flows to comprehensively analyze the road traffic flow and vehicle structure in downtown beijing.A dynamic emission inventory of motor vehicle air pollutants in downtown beijing in 2021 was established,and the impact of these emissions on air quality was simulated and quantified,and different emission reduction control scenarios were proposed to evaluate their environmental improvement effects and explore measures to mitigate the impact of pollution *** results show that the high traffic flow and the structure of the motor vehicle emissions in downtown beijing are the main causes of severe motor vehicle *** data shows that traffic flow in central beijing is dominated by small passenger vehicles,while the vehicle mix is better than in other regions,with 72.0%of vehicles meeting"National V"or higher emission ***,to achieve higher air quality goals,further reducing vehicle emissions is *** on dynamic traffic flow,the average daily emissions of nitrogen oxides(NOX),particulate matters(PM_(2.5))and volatile organic compounds(VOC)from motor vehicles in central beijing are 17.7 tons,0.6 tons and 14.0 tons,respectively,accounting for 23.0%of the city’s average daily motor vehicle *** a zero-emission zone for motor vehicles were implemented in central beijing,the annual average emission level of pollutants will be reduced by 10.4%to 21.0%.The designation of ultra-low emission zones for motor vehicles could be effective in improving the air quality in the center of beijing.

关键词： Motor vehicle Air pollutant Emission characteristics Control strategy beijing