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EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation

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Science China(Information Sciences) 2024年第08期67卷 130-146页

作者： Yingjian LIU Jiang LI Xiaoping WANG Zhigang ZENG School of artificial intelligence and Automation Huazhong University of Science and Technology Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education Institute of artificial intelligence Huazhong University of Science and Technology

Emotion recognition in conversation(ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies. In this paper,we propose an emotional inertia and contagion-driven dependency modeling approach(EmotionIC) for ERC tasks. Our EmotionIC consists of three main components, i.e., identity masked multi-head attention(IMMHA), dialogue-based gated recurrent unit(DiaGRU), and skip-chain conditional random field(SkipCRF).Compared to previous ERC models, EmotionIC can model a conversation more thoroughly at both the feature-extraction and classification levels. The proposed model attempts to integrate the advantages of attention-and recurrence-based methods at the feature-extraction level. Specifically, IMMHA is applied to capture identity-based global contextual dependencies, while Dia GRU is utilized to extract speaker-and temporal-aware local contextual information. At the classification level, SkipCRF can explicitly mine complex emotional flows from higher-order neighboring utterances in the conversation. Experimental results show that our method can significantly outperform the state-of-the-art models on four benchmark *** ablation studies confirm that our modules can effectively model emotional inertia and contagion.

关键词： emotion recognition in conversation emotional inertia and contagion multi-head attention gated recurrent unit conditional random field

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A Hybrid and Inexact Algorithm for Nonconvex and Nonsmooth Optimization

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Journal of Systems Science & Complexity 2024年

作者： WANG Yiyang SONG Xiaoliang college of artificial intelligence Dalian Maritime University School of Mathematical Sciences Dalian University of Technology

The problem of nonconvex and nonsmooth optimization (NNO) has been extensively studied in the machine learning community,leading to the development of numerous fast and convergent numerical *** algorithms typically employ unified iteration schemes and require explicit solutions to subproblems for ensuring ***,these inflexible iteration schemes overlook task-specific details and may encounter difficulties in providing explicit solutions to *** contrast,there is evidence suggesting that practical applications can benefit from approximately solving subproblems;however,many existing works fail to establish the theoretical validity of such *** this paper,the authors propose a hybrid inexact proximal alternating method (hiPAM),which addresses a general NNO problem with coupled terms while overcoming all aforementioned *** proposed hiPAM algorithm offers a flexible yet highly efficient approach by seamlessly integrating any efficient methods for approximate subproblem solving that cater to ***,the authors have devised a simple yet implementable stopping criterion that generates a Cauchy sequence and ultimately converges to a critical point of the original NNO *** proposed numerical experiments using both simulated and real data have demonstrated that hiPAM represents an exceedingly efficient and robust approach to NNO problems.

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A Novel Predictive Model for Edge Computing Resource Scheduling Based on Deep Neural Network

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 259-277页

作者： Ming Gao Weiwei Cai Yizhang Jiang Wenjun Hu Jian Yao Pengjiang Qian School of artificial intelligence and Computer Science Jiangnan UniversityWuxi214122China The Center for Intelligent Systems and Applications Research School of Artificial Intelligence and Computer ScienceJiangnan UniversityWuxi214122China School of Information Engineering Huzhou UniversityHuzhou313000China

Currently,applications accessing remote computing resources through cloud data centers is the main mode of operation,but this mode of operation greatly increases communication latency and reduces overall quality of service(QoS)and quality of experience(QoE).Edge computing technology extends cloud service functionality to the edge of the mobile network,closer to the task execution end,and can effectivelymitigate the communication latency ***,the massive and heterogeneous nature of servers in edge computing systems brings new challenges to task scheduling and resource management,and the booming development of artificial neural networks provides us withmore powerfulmethods to alleviate this ***,in this paper,we proposed a time series forecasting model incorporating Conv1D,LSTM and GRU for edge computing device resource scheduling,trained and tested the forecasting model using a small self-built dataset,and achieved competitive experimental results.

关键词： Edge computing resource scheduling predictive models

ContextAug:model-domain failing test augmentation with contextual information

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Frontiers of Computer Science 2024年第2期18卷 43-60页

作者： Zhuo ZHANG Jianxin XUE Deheng YANG Xiaoguang MAO School of Information Technology and Engineering Guangzhou College of CommerceGuangzhou 511363China School of Computer and Information Engineering Institute for Artificial IntelligenceShanghai Polytechnic UniversityShanghai 201209China college of Computer National University of Defense TechnologyChangsha 410073China

In the process of software development,the ability to localize faults is crucial for improving the efficiency of *** speaking,detecting and repairing errant behavior at an early stage of the development cycle considerably reduces costs and development *** have tried to utilize various methods to locate the faulty ***,failing test cases usually account for a small portion of the test suite,which inevitably leads to the class-imbalance phenomenon and hampers the effectiveness of fault ***,in this work,we propose a new fault localization approach named *** obtaining dynamic execution through test cases,ContextAug traces these executions to build an information model;subsequently,it constructs a failure context with propagation dependencies to intersect with new model-domain failing test samples synthesized by the minimum variability of the minority feature *** contrast to traditional test generation directly from the input domain,ContextAug seeks a new perspective to synthesize failing test samples from the model domain,which is much easier to augment test *** conducting empirical research on real large-sized programs with 13 state-of-the-art fault localization approaches,ContextAug could significantly improve fault localization effectiveness with up to 54.53%.Thus,ContextAug is verified as able to improve fault localization effectiveness.

关键词： context fault localization test cases

Blockchain-Based Message Authentication Scheme for Internet of Vehicles in an Edge Computing Environment

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Computer Systems Science & Engineering 2024年第5期48卷 1301-1328页

作者： Qiping Zou Zhong Ruan Huaning Song college of artificial intelligence and Manufacturing Hechi UniversityYizhou546300China college of Big Data and Computer Hechi UniversityYizhou546300China

As an important application of intelligent transportation system,Internet of Vehicles(IoV)provides great convenience for *** can obtain real-time traffic conditions through the IoV’s services,plan users’travel routes,and improve travel ***,in the IoV system,there are always malicious vehicle nodes publishing false ***,it is essential to ensure the legitimacy of the *** addition,during the peak period of vehicle travel,the vehicle releases a large number of messages,and IoV authentication efficiency is prone to performance *** existing authentication schemes have the problem of low authentication efficiency in the *** address the above problems,this paper designs a novel reliable anonymous authentication scheme in IoV for Rush-hour ***,our scheme uses blockchain and elliptic curve cryptography(ECC)to design authentication algorithms for message authentication between vehicles and roadside units(RSU).Additionally,we introduce the idea of edge computing into the scheme,RSU will select themost suitable vehicle as the edge computing node for message *** addition,we used the ProVerif tool for Internet security protocols and applications to test its security,ensuring that it is secure under different network *** the simulation experiment,we compare our scheme with other existing *** scheme has a significant improvement in computational overhead,authentication efficiency and packet loss rate,and is suitable for traffic scenarios with large message volume.

关键词： Internet of Vehicles messages authentication edge computing blockchain elliptic curve cryptography

RecBERT:Semantic recommendation engine with large language model enhanced query segmentation for k-nearest neighbors ranking retrieval

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Intelligent and Converged Networks 2024年第1期5卷 42-52页

作者： Richard Wu the Dublin Unified School District and the SF artificial intelligence Club DublinCA 94568USA

The increasing amount of user traffic on Internet discussion forums has led to a huge amount of unstructured natural language data in the form of user *** modern recommendation systems rely on manual tagging,relying on administrators to label the features of a class,or story,which a user comment corresponds *** common approach is to use pre-trained word embeddings to compare class descriptions for textual similarity,then use a distance metric such as cosine similarity or Euclidean distance to find top k ***,neither approach is able to fully utilize this user-generated unstructured natural language data,reducing the scope of these recommendation *** paper studies the application of domain adaptation on a transformer for the set of user comments to be indexed,and the use of simple contrastive learning for the sentence transformer fine-tuning process to generate meaningful semantic embeddings for the various user comments that apply to each *** order to match a query containing content from multiple user comments belonging to the same class,the construction of a subquery channel for computing class-level similarity is *** channel uses query segmentation of the aggregate query into subqueries,performing k-nearest neighbors(KNN)search on each individual *** achieves state-of-the-art performance,outperforming other state-of-the-art models in accuracy,precision,recall,and F1 score for classifying comments between four and eight classes,*** outperforms the most precise state-of-the-art model(distilRoBERTa)in precision by 6.97%for matching comments between eight classes.

关键词： sentence transformer simple contrastive learning large language models query segmentation k-nearest neighbors

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi AL-MEKHLAFI Shiguang LIU college of intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu Hui Zeng Bin Fan the School of intelligence Science and Technology and the Institute of artificial intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

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Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 446-458页

作者： Nuo Chen Linjing Li Wenji Mao School of artificial intelligence University of Chinese Academy of SciencesBeijing 100049 Institute of Automation Chinese Academy of SciencesBeijing 100190China

The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players usually move in three-dimensional space with a three-degree-of-freedom control. In this paper,we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game, in which the pursuer follows a three-degree-of-freedom control, and the evader moves freely. First, we describe the pursuer's three-degree-of-freedom control and the evader's relative coordinate. We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs(HJBI) method, which divides the pursuit-evasion process into the navigation and acceleration phases. Besides, we analyze the maximum allowable speed for the pursuer to capture the evader successfully and provide the strategy with which the evader can escape when the pursuer's speed exceeds the threshold. We further conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.

关键词： Differential game equilibrium strategy pursuit-evasion game threedegree-of-freedom control

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