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Cross-Modality Disentangled Information Bottleneck Strategy for Multimodal Sentiment Analysis

Cross-Modality Disentangled Information Bottleneck Strategy ...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Deng, Zhengnan Huang, Guoheng Zhong, Guo Yuan, Xiaochen Huang, Lian Pun, Chi-Man School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510420 China Macao Polytechnic University Faculty of Applied Sciences 999078 China Guangdong Mechanical and Electrical College Department of Applied Electronics Guangzhou510515 China University of Macau Department of Computer and Information Science China

ISBN: (纸本)9781665410205

Multimodal Sentiment Analysis (MSA) has been a pivotal domain in current research area which utilizes diverse information carriers such as videos containing multiple modal-ities to understand the user's sentiment. With the success of multimodal fusion techniques, lots of fusion strategies have been proposed to obtain a favorable multimodal joint representation for MSA. However, existing studies hardly consider the problem of redundant information in unimodal, resulting in the joint representation may contain much redundant information from different modalities, thus limiting the accuracy of sentiment prediction. In this work, we propose a Cross-Modality Disentangled Information Bottleneck Strategy (CMDIBS), which consists of a Cross-Modality Knowledge Awareness (CMKA) module and a Multimodal Disentangled Information Bottleneck (MDIB) mechanism. Specifically, the CMKA module encourages in-teractions among different modalities to learn the sentiment embedding relevant to the predicted goals. In particular, MDIB mechanism aims to maximize the mutual information (MI) between the multimodal joint representation and the predicted label, and maximize the MI between the style embedding with the label and the input data while constraining the MI between the multimodal joint representation and the style embedding to obtain a succinct and efficient multimodal joint representation. Experimental results on the benchmark datasets, namely CMU-MOSI and CMU-MOSEI, indicated that the proposed method surpasses existing approaches and attains SOTA performance. © 2024 IEEE.

关键词： Benchmarking

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Fault detection method of power cable terminal based on infrared thermal imaging signal reconstruction 2

Fault detection method of power cable terminal based on infr...

引用

2023 2nd International Conference on Energy and Electrical Power Systems, ICEEPS 2023

作者： Li, Yan Gao, Yihang School of Transportation Information Jilin Communications Polytechnic Jilin Changchun130015 China College of Computer Science and Technology Heilongjiang University Heilongjiang Harbin150006 China

Considering the low efficiency of traditional fault detection methods, this paper proposes a power cable terminal fault detection method based on infrared thermal imaging signal reconstruction. The method includes the following steps: first, establish the thermal resistance network structure of the power cable terminal to obtain the structural relationship between terminal components;second, collect operational data of the power cable terminal and perform calculations;finally, use an infrared imager to capture the infrared radiation of the power cable terminal and obtain fault detection results based on the calculation results. Experiments show that the detected results of this method are completely consistent with the actual situation, with an accuracy rate of up to 99%, and can achieve high-precision detection of power cable terminal faults. © Published under licence by IOP Publishing Ltd.

关键词： Fault detection

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A Novel Circuit and Layout Design of SEU Tolerant SRAM in a 65nm CMOS Process 18

A Novel Circuit and Layout Design of SEU Tolerant SRAM in a ...

引用

18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Lai, Xiaoling Guo, Yangming Zhang, Jian Ju, Ting Zhu, Qi Zhou, Guochang Northwestern Polytechnic University School of Computer Science Xi'an China Xi'an Branch of China Academy of Space Technology Xi'an China

ISBN: (纸本)9798350312201

In order to address the vulnerability of embedded SRAMs to single event soft errors due to high-energy particles in a space radiation environment, this paper proposes a novel circuit d layout design of SEU tolerant SRAM based on a DICE structure. A DICE SRAM design with a depth of 4096 and a bit width of 12 is completed based on a commercial 65nm bulk silicon CMOS process, implemented using 3 layers of metal, with an area only 1.6 times that of a non-DICE SRAM. Circuit and irradiation simulation results illustrate that the SRAM has an access time of less than 2.2ns and a single event upset cross section of 1.74×10-13 cm2/bit at an equivalent LET value of 55.3 MeV/mg/cm2 of particle incidence. The SRAM circuit's performance and resistance to single-particle soft errors can significantly reduce the area, wiring resources and timing overhead associated with hardening the embedded SRAM circuit in radiation hardened ASIC designs. © 2023 IEEE.

关键词： Heavy ions

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Two-step Thompson Sampling for Multi-Armed Bandit Problem 43

Two-step Thompson Sampling for Multi-Armed Bandit Problem

引用

43rd Chinese Control Conference, CCC 2024

作者： Shang, Zhigang Yang, Lifang Li, Mengmeng Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9789887581581

An important feature of sequential decision-making under uncertain conditions is to strike a balance between exploration (obtaining information about the value of actions) and utilization (selecting the best action based on existing knowledge). The multi-armed bandit is a classic task for balancing their relationship. As the agent has learnt the relationship between two options in a 2-armed bandit task, it will no longer explore but instead use them directly. Inspired by the research, an algorithm based on two-step Thompson sampling (T-TS) is proposed to solve multi-armed bandit problem. First, posterior Beta distributions for the reward of each arm and the probability of the superior arm were established respectively. In the first-step TS, Thompson sampling was used to extract the maximum value from the posterior distribution of probability for the superior arm, determining it as the selected arm. In the two-step TS, Thompson sampling was used to sample from the distributions of the reward. During the updating, the posterior distribution of the probability for the superior arm was updated based on observations including actions and reward, and the distribution of the reward was updated based on the reward feedback. We performed the comparative experiments to solve the static multi-bandit tasks with 10, 20, 40, and 80 arms respectively by the state-of-the-art B-UCB algorithm, Thompson sampling and the proposed T-TS. The results shown that our proposed T-TS can learn the superior action more quickly with the best robustness. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Importance sampling

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A Preliminary Study of Wisdom Teaching for 'Information technology' Course 5

A Preliminary Study of Wisdom Teaching for 'Information Tech...

引用

5th International Conference on computer science and Technologies in Education, CSTE 2023

作者： Liu, Xiaoli Zhang, Fan Fan, Zuzhi Gu, Shiqian College of Information Science and Technology Jinan University Guangzhou China Mathematics and Computer Science School Wuhan Polytechnic University Wuhan China School of Information Science and Technology Jinan University Guangzhou China School of Public Administration Jinan University Guangzhou China

ISBN: (纸本)9798350325720

Smart education has become an important direction of future education, but the improvement and practice of wisdom teaching is a long process. In this paper, we present the available teaching platforms that support wisdom teaching of Jinan university, and carry out teaching implementation, show the effect of the initial exploration of the wisdom teaching of the 'Information technology' course. © 2023 IEEE.

关键词： Teaching

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Digital interpretation of Tai Chi basic skills based on surface electromyography feature analysis 4

Digital interpretation of Tai Chi basic skills based on surf...

引用

4th International Conference on Biomedicine and Bioinformatics Engineering, ICBBE 2024

作者： Li, Mengmeng Gu, Zhiyuan Wan, Hong School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9781510682443

Basic Tai Chi exercises serve as the foundation and core of Tai Chi practice. A deep understanding of the movement principles and essential characteristics is crucial to ensuring the effectiveness of training. However, practitioners often struggle to grasp the essentials, resulting in minimal progress or even injuries that may lead them to abandon the practice. To achieve a digital interpretation of the movement transitions and force application principles in basic Tai Chi exercises, we introduced surface electromyography (sEMG) detection into basic Tai Chi in this study. Eight Tai Chi experts were invited to construct an expert subject dataset. Then we extracted and analyzed the integral whole electric value and contribution rates of relevant muscles in basic Kai He Gong (KHG) exercise, as well as the dynamic changes on both sides of the body. An improved Teager-Kaiser Energy (TKE) algorithm was used to accurately identify the muscle force sequencing in expert-level and trainee-level basic movement. The results revealed that the cooperated relationship the left and right body sides and the crucial role of the erector spinae in the waist connecting the upper and lower limbs in the KHG exercises, demonstrating the Tai Chi principle of "controlling from the waist". In all, we explored the sEMG activity patterns in basic Tai Chi exercises in this study, enabling a digital interpretation of movement transitions and muscle force application principles. The results could provide references for the training and teaching of basic Tai Chi exercises. © 2024 SPIE.

关键词： Electromyography

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SoulMate: Short-Text Author Linking Through Multi-Aspect Temporal-Textual Embedding (Extended Abstract) 40

SoulMate: Short-Text Author Linking Through Multi-Aspect Tem...

引用

40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Najafipour, Saeed Hosseini, Saeid Hua, Wen Kangavari, Mohammad Reza Zhou, Xiaofang School of Information Technology and Electrical Engineering Iran University of Science and Technology Tehran Iran Sohar University Faculty of Computing and Information Technology Sohar Oman Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350317152

We devise a neural network-based temporal-textual framework that generates subgraphs with highly correlated authors from short-text contents. Our approach computes the relevance score (edge weight) between authors by considering a portmanteau of contents and concepts. It then employs a stack-wise graph-cutting algorithm to extract communities of related authors. Experimental results show that our multi-aspect vector space model can gain higher performance than other knowledge-centered competitors in linking short-text authors. © 2024 IEEE.

关键词： Semantics

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Striatal Local Field Potential Dynamics During Decision-Making Learning in Pigeons 24

Striatal Local Field Potential Dynamics During Decision-Maki...

引用

16th International Conference on Bioinformatics and Biomedical technology, ICBBT 2024

作者： Jin, Fuli Wang, Yinghui Shang, Zhigang School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9798400717666

Decision-making is a complex cognitive process vital for the survival and adaptive behavior of species, and the neural mechanisms behind this behavior have been the focus of extensive *** striatum is a key region in the brain that plays a crucial role in the decision-making process, making it an ideal candidate for investigating the neural correlates of learning and *** study aims to explore the changes in the striatum and its local field potentials (LFPs) during the learning of decision-making, providing potential insights into the role of the striatum in decision-making in *** study simultaneously collected behavior data and striatal LFPs from 4 pigeons during a three-armed bandit *** pigeons' learning process, behavioral accuracy, reward probabilities, and"win-stay-lose-shift" characteristics were *** power changes in six different frequency bands of striatal LFPs between the early and late stages of learning were *** pigeons' learning process significantly modulated the power in the Beta frequency band, indicating its crucial role in ***, the power of the Theta, Alpha, and Beta bands correlated with choices suggesting a high reward probability, emphasizing the relationship between reward probability and the modulation of power in the *** study sheds light on the neural processes underlying decision-making in pigeons, demonstrating the modulation of LFP power in the striatum and its relationship to reward *** findings contribute to our understanding of decision-making processes in animals. © 2024 Copyright held by the owner/author(s).

关键词： Decision making

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Short-Text Author Linking Through Multi-Facet Temporal-Textual Embedding (Extended Abstract) 40

Short-Text Author Linking Through Multi-Facet Temporal-Textu...

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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Najafipour, Saeed Najafipour Hosseini, Saeid Hua, Wen Reza Kangavari, Mohammad Zhou, Xiaofang School of Information Technology and Electrical Engineering Iran University of Science and Technology Tehran Iran Sohar University Faculty of Computing and Information Technology Sohar Oman The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong University of Science and Technology Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9798350317152

关键词： Semantics

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Dp-graph2vec: Learning Differential Privacy Representations of Graphs 7

Dp-graph2vec: Learning Differential Privacy Representations ...

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7th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Su, Hengdi Sang, Yingpeng Shen, Hong School Of Computer Science And Engineering Sun Yat-sen University Guangzhou China School Of Engineering And Technology Central Queensland University Brisbane Australia Macao Polytechnic University Faculty Of Applied Sciences Macau China

ISBN: (纸本)9798350361445

Many machine learning tasks based on graph embedding achieved significant results in a wide range of fields, such as node clustering and link prediction. However, the original graph data may contain confidential information about individuals or organizations, which could be revealed through the publication of graphs or even via embeddings of graphs. While datasets contain highly private sensitive information, graph embedding methods which do not consider any privacy protection measures become impractical. Researchers recently have explored how differential privacy can be employed to a number of machine learning tasks, but differential privacy embedding methods for graphs have not been considered yet to the best of our knowledge. To address this problem, we propose a differential privacy embedding methods for graphs, named dp-graph2vec, based on gradient perturbation. In dp-graph2vec, we design a training mechanism called Average-Negative Sampling Update(ANSU) to solve the problem of privacy accounting. We proved that the mechanism satisfies the definition of differential privacy. Finally, we demonstrated results on various public datasets. Experiments and theory show that dp-graph2vec can strike a balance between privacy protection and data utility. © 2024 IEEE.

关键词： Data mining

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