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Conditional selection with CNN augmented transformer for multimodal affective analysis

CAAI Transactions on Intelligence Technology 2024年第4期9卷 917-931页

作者： Jianwen Wang Shiping Wang Shunxin Xiao Renjie Lin Mianxiong Dong Wenzhong Guo College of Computer and Data Science Fuzhou UniversityFuzhouChina College of Computer and Cyber Security Fujian Normal UniversityFuzhouChina Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhouChina Digital Fujian Institute of Big Data Security Technology Fujian Normal UniversityFuzhouChina Department of Sciences and Informatics Muroran Institute of TechnologyMuroranJapan

Attention mechanism has been a successful method for multimodal affective analysis in recent years. Despite the advances, several significant challenges remain in fusing language and its nonverbal context information. One is to generate sparse attention coefficients associated with acoustic and visual modalities, which helps locate critical emotional se-mantics. The other is fusing complementary cross‐modal representation to construct optimal salient feature combinations of multiple modalities. A Conditional Transformer Fusion Network is proposed to handle these problems. Firstly, the authors equip the transformer module with CNN layers to enhance the detection of subtle signal patterns in nonverbal sequences. Secondly, sentiment words are utilised as context conditions to guide the computation of cross‐modal attention. As a result, the located nonverbal fea-tures are not only salient but also complementary to sentiment words directly. Experi-mental results show that the authors’ method achieves state‐of‐the‐art performance on several multimodal affective analysis datasets.

关键词： affective computing data fusion information fusion multimodal approaches

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Enhanced Discriminant Analysis Based Fault Diagnosis Scheme for Marine Diesel Engines 11

Enhanced Discriminant Analysis Based Fault Diagnosis Scheme ...

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11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Zhong, Kai Wang, Jiayi Pan, Donghui Institutes of Physical Science and Information Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Anhui Hefei230601 China School of Mathematical Science Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Hefei230601 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Since the marine diesel engine is one of the most popular power equipments for modern shipping, accurate and timely diagnose the faults occurred in diesel engine is extraordinary important for long service life and high reliability. Note that Fisher discriminant analysis (FDA) has been widely applied in fault diagnosis field. However, it is quite susceptible to the small sample size (SSS) problem, which is very common in the running process of diesel engine. In response to the problem, this study pro-poses a new fault classification criterion based exponential discriminant analysis (EDA) scheme for diesel engine fault diagnosis, in which the exponential transformation is carried out first to enlarge the margin between different classes, thus the different fault classes are further separated and the diagnosis capability is enhanced. In addition, the theorems of matrix exponential guarantee that the matrix exp (Sw) is always full-rank, even though the Sw is singular. That means, the novel methodology is still appli-cable when confronts with the SSS problem. Finally, based on the more reasonable fault classification criterion, the simulation results on a real-world two-stroke six-cylinder low-speed marine diesel engine indicate that the EDA based diagnosis scheme achieves higher fault diagnosis accuracy with good robustness and practicability in real-world engineering applications. © 2022 IEEE.

关键词： Failure analysis

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Practical Teaching Reform of Programming Courses Based on Online Coding Platforms 18th

Practical Teaching Reform of Programming Courses Based on On...

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18th International Conference on Computer Science and Education, ICCSE 2023

作者： Yuan, Guowu Yue, Kun Hu, Kuang School of Information Science and Engineering Yunnan University Yunnan Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan Kunming650504 China

ISBN: (纸本)9789819707904

Programming proficiency stands as one of the most vital competencies for students majoring in computer-related disciplines. This paper scrutinizes the issues prevailing in the cultivation of programming skills. Notably, it emphasizes an imbalance in teaching, whereby concepts and syntax receive undue attention while hands-on programming experiences are inadequately incorporated. Furthermore, the absence of standardized assessment mechanisms and avenues for advanced students to enhance their skills compounds these challenges. To augment students’ programming capabilities, we have established an online coding platform, facilitating a practical teaching reform in programming courses guided by "learning, practicing, certification and competing". "Learning" entails knowledge learning, "practicing" involves extensive programming practicing, "certification" signifies reaching programming competency standards, and "competing" denotes participation in programming competitions to enhance skill sets. Over seven years, this implementation has markedly improved students’ programming prowess. It has also led to advancements in certified software professional (CSP) and various programming competition outcomes, effectively embodying the "promoting learning and teaching through competitions" philosophy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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MoCap-Video Data Retrieval with Deep Cross-Modal Learning 30th

MoCap-Video Data Retrieval with Deep Cross-Modal Learning

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30th International Conference on MultiMedia Modeling, MMM 2024

作者： Zhang, Lu Peng, Jingliang Lv, Na Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China School of Information Science and Engineering University of Jinan Jinan China

ISBN: (纸本)9783031533075

Cross-modal retrieval between video and motion capture (MoCap) data facilitates efficient reuse of human motion data in either skeletal or video format. For this purpose, we propose a deep cross-modal learning model for cross-modal retrieval between MoCap data and video data. First, we use a graph convolution-based network and a 3D convolution-based network to extract features from MoCap data and video data, respectively. In addition, we propose to use a pre-defined common subspace to maximize the inter-class variation and minimize the intra-class variation. Furthermore, we employ a similarity matrix to achieve the alignment between these two modalities and exploit their underlying correlations. For the purpose of experimental evaluation, due to the small amount of video data corresponding to the MoCap data in the public HDM05 dataset, we recorded a video dataset corresponding to the HDM05 motion capture dataset and performed cross-modal retrieval on it. The experimental results proved the effectiveness of the proposed scheme. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

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Research on Infrared Pedestrian and Vehicle Detection Algorithm from the Perspective of UAV - Small target detection based on YOLOv8 24

Research on Infrared Pedestrian and Vehicle Detection Algori...

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3rd International Conference on Computer, Artificial Intelligence and Control Engineering, CAICE 2024

作者： Li, Jinfeng Ma, Long Zhu, Jing Yue, Yurong Zhao, Dan Shan, Wei Dong, Xuan School of Physics and Electronic Information Huaibei Normal University Anhui Provincial Key Laboratory of Intelligent Computing and Application 100 Dongshan Road Huaibei235000 China

ISBN: (纸本)9798400716942

In the infrared pedestrian and vehicle target detection task from the perspective of UAV, there are problems such as small target size and ambiguous scale features, which can easily lead to underdetection and false detection. An improved small target detection algorithm YOLOv8 was proposed. On the basis of YOLOv8, a small target detection layer is added as the fourth output layer, which can detect smaller targets. Experimental results indicate that in the HIT-UAV dataset experiment, the accuracy P, recall R and average accuracy (mAP) of the improved algorithm are 84.9%, 72.3%, 77.7% and 51.7%, respectively, which are improved by 5.7%, 6.4%, 7% and 6.1% compared with the original YOLOv8 network, respectively. The detection accuracy of small targets is improved, and the effectiveness verification of the network is improved. © 2024 ACM.

关键词： Target tracking

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MMT: Transformer for Multi-modal Multi-label Self-supervised Learning

MMT: Transformer for Multi-modal Multi-label Self-supervised...

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International Conference on Image, Vision and intelligent Systems, ICIVIS 2023

作者： Wang, Jiahe Li, Jia Liu, Xingrui Gao, Xizhan Niu, Sijie Dong, Jiwen School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network-Based Intelligent Computing Jinan250022 China

ISBN: (纸本)9789819708543

We proposed a novel network, called Transformer, for Multi-modal Multi-label Self-Supervised Learning (MMT) in the context of video classification. Our approach tackles the input challenges arising from different modalities by incorporating auxiliary tasks that exploit the natural synchronization and correlation between video, audio, and text. To bridge the semantic gap existing among modalities, we perform alignment in both high-dimensional and low-dimensional feature spaces for video-audio and video-text modalities, respectively. Moreover, we introduce a contrastive loss to enhance the proximity of semantically related samples, effectively catering to the specific requirements of multi-modal learning. The experimental results demonstrate that our method achieves competitive performance in various video classification tasks. This demonstrates the effectiveness of our proposed Transformer network for MMT, showcasing its potential in advancing multi-modal learning research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Supervised learning

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GAN-Based Covert Communications Against an Adversary with Uncertain Detection Threshold in Federated Learning Networks

GAN-Based Covert Communications Against an Adversary with Un...

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2023 International Conference on Networking and Network Applications, NaNA 2023

作者： Feng, Yu Jiang, Yu'e Wang, Yutong Anhui Province School of Computer and Information Anqing Normal University University Key Laboratory of Intelligent Perception and Computing Anqing China

ISBN: (纸本)9798350327380

Federated learning (FL) is a promising distributed machine learning paradigm that can address privacy and security issues in the Internet of Things, Beyond 5G and 6G, and so on. Typically, numerous mobile devices in the FL network enable the server to complete model aggregation by uploading trained models obtained from local data. However, due to the broadcast nature of wireless channels, this upload process is vulnerable to adversary's monitoring or potential attacks, and it becomes one of the important risks of model leakage. Physical layer covert communications can protect the existence of covert signals or links, which is one of the effective methods to protect this model uplink. Furthermore, when there is an adversary with an uncertain detection threshold in the network, there is a competitive game between the adversary and mobile devices, which poses a challenge to the transmit power design of covert schemes. Considering the dynamic competition process in covert communications is similar to the zero-sum game process between discriminators and generators in Generative Adversarial Networks (GANs). Therefore, we propose a GAN-based physical layer covert communications against the adversary and protect the uplink in the FL networks. Moreover, the generator imitates the mobile device and the discriminator imitates the adversary. Both are constructed using neural networks, and the learning optimization process is achieved through a zero-sum game between them. Experiment results show that the designed algorithm is convergent and can obtain the optimal covert transmit power and the maximum average communication rate. © 2023 IEEE.

关键词： Generative adversarial networks

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Chinese fable generation based on large scale pretrained language models 3

Chinese fable generation based on large scale pretrained lan...

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3rd International Symposium on Computer Applications and information Systems, ISCAIS 2024

作者： Jing, Rong Wan, Fucheng Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730030 China Key Laboratory of China's Ethnic Languages and Intelligent Processing of Gansu Province Northwest Minzu University Gansu Lanzhou China

ISBN: (纸本)9781510681316

Story generation is an important part of natural language processing, text generation tasks have received extensive attention from scholars in recent years. Existing methods are difficult to generate complete, logically fluent texts with low repetition rate based on a given outline vocabulary. To solve this problem, based on the dataset generated from outline conditional stories, we use the latest GLM model and instruct-tuning to generate Chinese fables and compare it with other big model fine-tuning with different parameter settings, and the experimental results show that the fables generated by Instruct-tuning have stronger logic and lower repetition rate. The models we used showed an increase of 1.5%, 2.43%, 1.51%, 3.25%, and 2.09% over the baseline model on the Blue-2, distinct-3, distinct-2, distinct-3, and distinct-4 metrics. © 2024 SPIE.

关键词： Natural language processing systems

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An ultra-wideband high-isolation dual-port MIMO antenna design

An ultra-wideband high-isolation dual-port MIMO antenna desi...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Cao, Shuangqing Li, Minquan Zi, Zhenfa Li, Zhonghui Anhui University Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Hefei230601 China Hefei Normal University School of Physics and Materials Engineering Hefei230601 China

ISBN: (纸本)9798350355581

In this paper, an antenna for ultra-wideband multiple-input and multiple-output (UWB-MIMO) is designed. The design comprises two hexagonal monopole antennas. In order to achieve ultra-wideband characteristics and mitigate the coupling, a stepped microstrip line structure for impedance matching and T-shaped defective ground structure are employed, which optimizes the broadband characteristics and achieves high isolation characteristics. The antenna achieves a wide impedance bandwidth of 3.5 GHz to 13.9 GHz (relative bandwidth of 119%). Furthermore, the isolation between the two feed ports of the antenna exceeds 18 dB, the envelope correlation coefficient (ECC) is less than 0.012, and it exhibits favorable radiation characteristics. © 2024 IEEE.

关键词： Bandwidth

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Development of a Universal RNA Dual-Terminal Labeling Method for Sensing RNA-Ligand Interactions

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CCS Chemistry 2023年第1期5卷 221-233页

作者： Longhuai Cheng Dejun Ma Jie Zhang Xueying Kang Yang Wu Yi Zhao Long Yi Zhen Xi State Key Laboratory of Elemento-Organic Chemistry Department of Chemical BiologyCollege of ChemistryNational Pesticide Engineering Research CenterCollaborative Innovation Center of Chemical Science and EngineeringNankai UniversityTianjin 300071 State Key Laboratory of Organic-Inorganic Composites and Beijing Key Laboratory of Bioprocess Beijing University of Chemical Technology(BUCT)Beijing 100029 Key Laboratory of Intelligent Information Processing Research Center for Ubiquitous Computing SystemsInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190

Dual labeling of an RNA can provide Förster resonance energy transfer(FRET)sensors for studying RNA folding,miRNA maturation,and RNA-protein ***,we report the development of a highly efficient strategy for direct dual-terminal labeling of any RNA of *** explored new Michael cycloaddition for facile labeling of 5′-terminal RNA with improved *** chemical tetrazinylation of RNA at the 3′-terminus was achieved with the highly efficient and catalysis-free tetrazine-cycloalkyne *** single-terminal labeling methods were combined for dual-terminal labeling of an RNA including short hairpin RNA,pre-miRNA,riboswitch,and noncoding ***,these dual-labeled RNA-based FRET sensors were used to monitor RNA-ligand interactions in vitro and in live *** is anticipated that these universal RNA labeling strategies will be useful to study RNA structures and functions.

关键词： dual labeling Förster resonance energy transfer sensor Michael cycloaddition tetrazinecycloalkyne ligation RNA-ligand interaction

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