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Multimodal Anti-Spoofing Emotion Recognition Using GRU and BERT 13

Multimodal Anti-Spoofing Emotion Recognition Using GRU and B...

引用

13th international conference of Information and Communication technology, ICTech 2024

作者： Ge, Changqiang Peng, Guofeng Guo, Ao Zhu, Wenbin Fan, Zhenhong Zhu, Xiaochun School of Automation Nanjing Institute of Technology Nanjing China School of Mechanical Engineering Nanjing Institute of Technology Nanjing China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350376258

Accurate recognition of human emotions is crucial for enhancing the effectiveness of human-computer interactions. This study addresses the limitations associated with using single-modal physiological signals by proposing a novel multimodal anti-spoofing emotion recognition model (MABer). The model integrates electroencephalogram (EEG), facial expression images, and heart rate signals, leveraging their complementary nature. It extracts temporal and spectral signatures from physiological signals by employing a bidirectional gated recurrent unit (GRU). Additionally, an asymmetric Transformer architecture is utilized for enhanced feature fusion and learning. The proposed model achieves superior performance when compared to existing methods, as demonstrated on the DEAP dataset. This study proposes a robust framework for identifying multimodal emotions based on physiological signals, facilitating the development of anti-spoofing intelligent human-computer interaction systems. ©2024 ieee.

关键词： Emotion Recognition

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Comparative Analysis of FinFET and 45nm CMOS technology in Adder Circuit Performance 5

Comparative Analysis of FinFET and 45nm CMOS Technology in A...

引用

5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Prameela, N.S. Bhaskar, Navaneeth Vijay, D. Shetty, Shravan N Shetty, Nishanth Kumar, Sujnan Sahyadri College of Engineering and Management Department of ECE Mangalore India

ISBN: (纸本)9798331518097

The paper presents a comprehensive comparative analysis of the implementations of a 16-transistor full-adder circuit using both 18nm FinFET and 45nm CMOS technologies. The effect of technology scaling on the intrinsic performance parameters of the circuit is analyzed in this study, with critical delay analysis defining overall performance and circuit speed. Designs were developed and simulated using Cadence Virtuoso. The designs were developed and simulated using Cadence Virtuoso. We used the Generic Process Design Kit (GPDK) 45nm and 18nm FinFET technology libraries. For delay and performance variations, transient analysis was performed. In the 45nm CMOS design, the full-adder circuit demonstrated reliable operation with a mean delay of moderate values, thus achieving a balance in power consumption and operational speed useful for a range of applications. On the other hand, the 18nm FinFET realization featured significant delay reductions, superior channel control abilities, and reduced leakage currents. This is specifically attributed to the inherent characteristics of FinFET structures. This makes FinFET a promising technology for low-power, high-speed applications that easily counter all the issues related to typical CMOS scaling. The paper thus focuses on the benefits of using FinFET technology while designing advanced Very Large-Scale Integration (VLSI). This brings significant insight into the optimization of a full-adder circuit that decreases power consumption along with improving processing speeds, thus allowing for more efficient Implementations in future technology nodes. © 2024 ieee.

关键词： CMOS integrated circuits

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Comprehensive Evaluation Method for User Green Attributes Considering Low-carbon Electricity Consumption Behavior

Comprehensive Evaluation Method for User Green Attributes Co...

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2024 international conference on Electrical Power systems and intelligent control, EPSIC 2024

作者： Wang, Jingting Wang, Yuyang Zhou, Ming Zhang, Xuesen Yu, Tao Chen, Chunyi Wu, Zhaoyuan School of Electrical and Electronic Engineering North China Electric Power University Beijing China Research Department State Grid Digital Technology Holding Co. Ltd. Beijing China State Grid Shanghai Municipal Electric Power Company Shanghai China

ISBN: (纸本)9798350366075

With the transformation and upgrading of China's energy system, many users offset their carbon emissions by purchasing green electricity and green certificate. Considering the current lack of a comprehensive carbon emission offset mechanism from low-carbon electricity consumption, determining the environmental value of low-carbon electricity and evaluating the green attributes of users are the primary challenges currently faced. To incentivize users to increasingly purchase low-carbon electricity, the theoretical framework for evaluating user’s low-carbon electricity consumption is established first based on the carbon flow tracing method and life-cycle theory. Then, based on AHP-entropy method and TOPSIS method, user green attributes evaluation model is construct including four different dimensions of evaluation indicators. Finally, case studies are conducted to analyze green attributes of multiple users considering low-carbon electricity consumption behavior patterns. ©2024 ieee.

关键词： Low emission

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Fault Location Analysis of Distribution Networks Considering intelligent Distributed Feeder automation 4

Fault Location Analysis of Distribution Networks Considering...

引用

4th international conference on Smart Power and Internet Energy systems (SPIES)

作者： Wu, Bin Zhang, Pan Zheng, Yue Wang, Zhaoyang Zhou, Xia Zhang, Tengfei State Grid Tianjin Elect Power Co Elect Power Res Inst Tianjin Peoples R China State Grid Tianjin Elect Power Co State Grid Tianjin Peoples R China Nanjing Univ Posts & Telecommun Coll Automat & Coll Artificial Intelligence Nanjing Peoples R China

ISBN: (纸本)9781665489577

Due to fibre constraints, the use of intelligent distributed feeder automation technology is limited in large-scale distribution networks, and feeder terminal devices are prone to information distortion due to environmental and other factors. Based on the above problems, this paper proposes an intelligent distributed feeder automation distribution network based on 5G communication. Firstly, based on the general architecture of distributed FA of 5G and the fault diagnosis method of distribution network with multi-agent mechanism, the screening of fault zones is carried out. Secondly, considering the end device information distortion, the Bayesian probability model fault segment is used to establish the evaluation function and find the optimal solution to complete the fault segment location. The simulation results show that this method can improve the fault tolerance of fault determination and effectively reduce the failure of fault determination due to FTU information distortion.

关键词： Distributed power new distribution networks information distortion Bayesian probability

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Photovoltaic Data Cleaning Method Based on DBSCAN Clustering, Quartile Algorithm and Pearson Correlation Coefficient Interpolation Method 6

Photovoltaic Data Cleaning Method Based on DBSCAN Clustering...

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6th international conference on Energy, Electrical and Power Engineering, CEEPE 2023

作者： Wang, Biyuan Deng, Xingye Chen, Taowei Li, Yidong Huizhou Power Supply Bureau Guangdong Power Grid Co Guangdong China School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798350348279

The proportion of photovoltaic power generation in the global energy structure is increasing year by year. Because of its volatility and periodicity, grid-connected photovoltaic challenges the safe and stable operation of power grid. One of the ways to solve this problem is data mining. Data mining needs high-quality data support, and data cleaning is one of the important means to improve data quality. Aiming at the problem of poor quality of original PV data, this paper analyzes two typical outliers of PV data and proposes a PV output data cleaning method based on Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, quartile algorithm and Pearson correlation coefficient interpolation method. Comparison of DBSCAN clustering algorithm combined with the quartile method of outlier identification with the quartile method alone outlier identification, the effectiveness of the method proposed in this paper is verified. Then using the method proposed in this paper for outlier identification based on Pearson correlation coefficient interpolation and cubic spline interpolation to verify the data filling effect, the results show that Pearson correlation coefficient interpolation is superior to cubic spline interpolation. Finally, two sets of data with different data cleaning methods are substituted into the Long short-term memory (LSTM) Model to verify accuracy of the cleaning method proposed in this paper. © 2023 ieee.

关键词： Data mining

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Application of Artificial Intelligence System Design Based on Genetic Algorithm In Horticultural Cultivation

Application of Artificial Intelligence System Design Based o...

引用

2023 ieee international conference on Integrated Circuits and Communication systems, ICICACS 2023

作者： Gao, Ri Ran, Liping Wu, Rongzhe Zong, Chengwen Cao, Li Aruna, M.T. Yanbian University Department of Horticulture and Garden Jilin China Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India

ISBN: (纸本)9798350398465

In order to change the situation that horticultural plants are severely limited by natural conditions, people gradually apply computer and Internet of Things technology to an artificial simulated intelligent greenhouse to simulate the environmental conditions suitable for plant growth. In gardening, we can use this method to optimize plant growth and improve productivity. This paper analyzes the application of artificial intelligence system design based on genetic algorithm in horticultural cultivation, studies and discusses the artificial intelligence control system from two aspects of hardware and software, looks for the artificial intelligence control system with low market price, good quality and high performance-price ratio, and constructs an intelligent system platform suitable for horticultural crop growth. © 2023 ieee.

关键词： Genetic algorithms

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Decentralized Event-Triggered Output Feedback control for Nonlinear Networked Interconnected systems under Multiple cyber Attacks

Decentralized Event-Triggered Output Feedback Control for No...

引用

ieee international conference on systems, Man, and cybernetics (SMC)

作者： Zhao, Ning Shi, Peng Zhang, Huiyan Harbin Engn Univ Intelligent Syst Sci & Engn Harbin 150001 Peoples R China Univ Adelaide Sch Elect & Elect Engn Adelaide SA 5005 Australia Chongqing Technol & Business Univ Natl Res Base Intelligent Mfg Serv Chongqing 400067 Peoples R China

ISBN: (纸本)9781665442077

This paper investigates the decentralized event-triggered output feedback control for nonlinear networked interconnected systems under multiple cyber attacks, where denial of service and deception attacks are considered. A resilient period event-triggered strategy is adopted to reduce the occupation of network resources. Considering the impact of cyber attacks, the output-based decentralized security controller is constructed within a unified framework. Sufficient conditions of stochastically finite-time stable of the switched system are given by employing the Lyapunov-Krasovskii functional. Then, the controller gains and event-triggered weight matrix are designed simultaneously. Finally, a chemical reactor system is used to substantiate the effectiveness of the proposed method.

关键词： Networked control systems

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Wireless Sensor Networks: Revolutionizing Explosive Detection 5

Wireless Sensor Networks: Revolutionizing Explosive Detectio...

引用

5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Sujith Kumar, P.S. Anand, C. Vasuki, N. Ramesh, V. Santhoshkumar, S.P. Sree Buddha College of Engineering Department of Computer Science and Engineering Kerala Alappuzha India Nandha College of Technology Department of Information Technology Erode India Government College of Engineering Department of Computer Science and Engineering Erode India School of Computing Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Avadi India

ISBN: (纸本)9798331518097

One of the important technologies for protecting civilian life from terrorist attacks is explosive detection techniques. The global incidence of terrorist activities has been considerably reduced by the development of explosive detection techniques, which has been made possible by ongoing technology improvements. Wireless sensor networks (WSNs) are one of these developments that has become an innovative tool for explosives detection. This work explores recent empirical research on the application of WSNs to explosives detection and includes statistical analysis of the investigations. Wireless sensor network with compatible specialized sensors is required for effective explosive detection. Three main wireless sensor system aspects that are relevant to explosives detection are covered in this research. It first looks at how scalable wireless sensors are in terms of explosives detection technologies. In the second section, it looks at the mobility and communication capabilities of WSNs and sensors in explosives detecting systems. Finally, it highlights potential hazards and weaknesses and addresses the crucial topic of data security inside wireless sensor networks used for explosive detection. The study also suggests incorporating drone assisted detection as a novel way to improve the coverage and effectiveness of explosives detection systems, adding to the continuous advancement of security technologies meant to shield civilian populations from terrorist threats. © 2024 ieee.

关键词： Terrorism

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An Interpretation on Brain Gate System Network and technology - A Study 1

An Interpretation on Brain Gate System Network and Technolog...

引用

1st ieee international conference on automation, Computing and Renewable systems, ICACRS 2022

作者： Sowmya, K. Sushitha, S. Department of MCA Nitte Meenakshi Institute of Technology Bangalore India

ISBN: (纸本)9781665460842

The process of thoughts-to-movement is a scientific discovery that makes a severely disabled human to manipulate a device using thoughts. These were achieved, in a great portion through the brain gate network technology. The network system uses a different kind of Brain neural signal which regulates the language of the neuron's sensing, transmission, perception, and implementation. The working idea of the brain gate system is that brainwave patterns are produced with brain function and not transmitted to the body. It is a brain implant device developed at Brown University in partnership with the biotech firm‚ cyber-Kinetics Neuroscience. Even though effective BCI research has been arrived in the past 25 years, this paper aims to study the working, core principles and research aspects of brain gate technology in depth. © 2022 ieee

关键词： Brain computer interface

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Proceedings - 2023 ieee international conference on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SocialCom/SustainCom 2023

Proceedings - 2023 IEEE International Conference on Parallel...

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21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big Data and Cloud Computing, 16th ieee international conference on Social Computing and Networking and 13th international conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

ISBN: (纸本)9798350329223

The proceedings contain 153 papers. The topics discussed include: transaction data management optimization based on multi-partitioning in blockchain systems;semi-asynchronous federated learning optimized for NON-IID data communication based on tensor decomposition;HKTGNN: hierarchical knowledge transferable graph neural network-based supply chain risk assessment;DQR-TTS: semi-supervised text-to-speech synthesis with dynamic quantized representation;deep reinforcement learning-based network moving target defense in DPDK;iNUMAlloc: towards intelligent memory allocation for AI accelerators with NUMA;and predictive queue-based low latency congestion detection in data center networks.

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