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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhibo Zhang Zhenyu Yang Yan Huang Baojie Xu Wenyue Hu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multimodal dialogue emotion recognition integrates data from multiple modalities to accurately identify emotional states in conversations. However, differences in expression and information density across modalities complicate the fusion of features. Traditional methods may introduce redundant information from other utterances, reducing the accuracy of emotion recognition. Existing one-hot labels often fail to capture the full range of emotional expressions, leading to biased results. To address these issues, we propose a model that fuses different modalities within the same utterance to avoid redundancy. It employs a progressive classification process, refining emotion recognition from coarse to fine granularity. Additionally, we use emotion polarity probabilities as weights for fine-grained classification and introduce a multimodal information-rich label that considers both the data and their interactions. Experiments on IEMOCAP and MELD datasets demonstrate the model’s effectiveness, significantly improving dialog emotion recognition accuracy. Our code is available at https://***/r/LOCG-188E.

关键词： Emotion recognition Accuracy Fuses Refining Termination of employment Speech recognition Signal processing Speech processing Optimization Faces

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Control of Master-Slave DC Microgrid with Optical Fiber Communication Link

Control of Master-Slave DC Microgrid with Optical Fiber Comm...

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International Renewable Energy Congress

作者： Asma Alfergani Farhat M. Shaltami Khalid Ateea Alfaitor Ashraf Khalil Faisal Mohamed Electrical and Electronics Engineering Department University of Benghazi Benghazi Libya College of Electrical and Electronics Technology – Benghazi Benghazi Libya Department of Computer Networks and Communications Faculty of Information Technology University of Benghazi Benghazi Libya DTU Engineering Technology Technical University of Denmark Kongens Lyngby Authority of Natural Science Research and Technology Tripoli Libya

ISBN: (数字)9798331516772

ISBN: (纸本)9798331516789

In this paper, a model for the master-slave DC Microgrid over a fiber optic link is proposed. The delay margin is calculated according to Lyapunov-Krasovskii functional using the LMI toolbox in Matlab with the binary iteration algorithm. The optical fiber link is implemented using optisystem simulator. The optical fiber link is set to transmit the digitalized reference current from master controller to the slave controller. The link tested at 100Mbps, 1Gbps and 2.5Gbps data rate values and several optical fiber lengths and wavelength of 1550nm and 1400nm. The results show that the performance of the link is sufficient at received power more than -30dBm for all data rate values at 1550nm. While at 1400nm, the attenuation rate is very high. Therefore, the link must be 10km to achieve acceptable performance. This wavelength is used in this simulation to avoid the C band and O band, which used for telecommunication purposes.

关键词： Optical fibers Renewable energy sources Sensitivity Delay effects Microgrids Receivers Main-secondary Stability analysis Delays MATLAB

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Cyber Security Posterior Distribution

Cyber Security Posterior Distribution

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Leo John Baptist Andrews Sampath Kumar Venkatachary D Sarathkumar Annamalai Alagappan M. Fathima Raymon Antony Raj R Rajeshkanna Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Electrical and Electronics Engineering Kongu Engineering College Erode district Tamilnadu India Grant Thornton Gaborone Botswana Department of Network and Infrastructure Management Faculty of Engineering and Technology Botho University Gaborone Botswana Department of EEE Thamirabarani Engineering College Tirunelveli Tamil Nadu India Department of Computer Science and Business Systems Sri Krishna College of engineering and Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350305463

ISBN: (纸本)9798350305470

Currently, the vast majority of international interactions and activities related to trade, government, culture, social interaction, and economics take place online. These interactions involve people, non-governmental organizations, governments, and government agencies at all levels. Recently, a sizeable number of commercial firms and government organizations all over the world have been presented with the challenge offered by cyberattacks as well as the danger represented by wireless communication technologies. A very little amount of time has passed since this had place. We were able to develop a model for the risk of cyber security by making use of Bayesian Networks. This model has the capability of locating the point of cyber security that is weak and merging two different cyber analysis models. Among these is the activityquality model, which shows how individuals and/or groups adhere to the legal requirements for cyber security. Evidence describing the critical component of cyber security for a research reactor's RPS may be produced via the cyber security risk model. An further model that shows the probability of a cyberattack against RPS architecture is the cyber security risk model.

关键词： Wireless communication Analytical models Government Sociology Cyberspace Safety Security

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3D Multi-Object Tracking Employing MS-GLMB Filter for Autonomous Driving

3D Multi-Object Tracking Employing MS-GLMB Filter for Autono...

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International Conference on Control, Automation and information Sciences (ICCAIS)

作者： Linh Van Ma Muhammad Ishfaq Hussain Kin-Choong Yow Moongu Jeon School of Electrical Engineering and Computer Science GIST Republic of Korea Large-scale AI Research Group Korea Institute of Science and Technology Information (KISTI) South Korea Faculty of Engineering and Applied Science University of Regina Canada

ISBN: (数字)9798331542047

ISBN: (纸本)9798331542054

The MS-GLMB filter offers a robust framework for tracking multiple objects through the use of multi-sensor data. Building on this, the MV-GLMB and MV-GLMB-AB filters enhance the MS-GLMB capabilities by employing cameras for 3D multi-sensor multi-object tracking, effectively addressing occlusions. However, both filters depend on overlapping fields of view from the cameras to combine complementary information. In this paper, we introduce an improved approach that integrates an additional sensor, such as LiDAR, into the MS-GLMB framework for 3D multi-object tracking. Specifically, we present a new LiDAR measurement model, along with a multi-camera and LiDAR multi-object measurement model. Our experimental results demonstrate a significant improvement in tracking performance compared to existing MS-GLMB-based methods. Importantly, our method eliminates the need for overlapping fields of view, broadening the applicability of the MS-GLMB filter. Our source code for nuScenes dataset is available at https://***/linh-gist/ms-glmb-nuScenes.

关键词： Laser radar Three-dimensional displays Source coding Buildings Radar tracking Cameras information filters Robustness Sensors Autonomous vehicles

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DasAtom: A Divide-and-Shuttle Atom Approach to Quantum Circuit Transformation

arXiv

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arXiv 2024年

作者： Huang, Yunqi Gao, Dingchao Ying, Shenggang Li, Sanjiang Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China

Neutral atom (NA) quantum systems are emerging as a leading platform for quantum computation, offering superior or competitive qubit count and gate fidelity compared to superconducting circuits and ion traps. However, the unique features of NA devices, such as long-range interactions, long qubit coherence time, and the ability to physically move qubits, present distinct challenges for quantum circuit compilation. In this paper, we introduce DasAtom, a novel divide-and-shuttle atom approach designed to optimise quantum circuit transformation for NA devices by leveraging these capabilities. DasAtom partitions circuits into subcircuits, each associated with a qubit mapping that allows all gates within the subcircuit to be directly executed. The algorithm then shuttles atoms to transition seamlessly from one mapping to the next, enhancing both execution efficiency and overall fidelity. For a 30-qubit Quantum Fourier Transform (QFT), DasAtom achieves a 415.8x improvement in fidelity over the move-based algorithm Enola and a 10.6x improvement over the SWAP-based algorithm Tetris. Notably, this improvement is expected to increase exponentially with the number of qubits, positioning DasAtom as a highly promising solution for scaling quantum computation on NA platforms. © 2024, CC BY.

关键词： Qubits

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Adaptive RBF-Neural-Network Control with Force Observer for Teleoperation Robotic System 1st

Adaptive RBF-Neural-Network Control with Force Observer for...

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1st International Conference on Cognitive Computation and Systems, ICCCS 2022

作者： An, Zhaohui Min, Gaochen Jiang, Xiangzuo Yu, Xinbo He, Wei Silvestre, Carlos School of Intelligence Science and Technology Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing100083 China Donald Bren School of Information and Computer Sciences University of California IrvineCA92697 United States Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China LARSyS Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (纸本)9789819927883

In this paper, an adaptive radial basis function neural network (RBFNN) control strategy is proposed for bilateral teleoperation robotic system with uncertainty and time delay. Meantime, the force observer method is used to estimate the interaction force between the slave robot and environment. The model of teleoperation robotic system is analyzed, and then the uncertainty of bilateral teleoperation robotic system is estimated by using RBFNN. Using Lyapunov stability theorem, the stability of teleoperation robotic system under our proposed control is proved. Finally, the effectiveness of the proposed control algorithm is verified by Matlab Simulink, and position tracking and force estimation performance of the teleoperation robotic system are guaranteed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time delay

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Enhancing Security in The Internet of Things Ecosystem using Reinforcement Learning and Blockchain

Enhancing Security in The Internet of Things Ecosystem using...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Akhtar Badshah Muhammad Waqas Shanshan Tu Ghulam Abbas Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and Technology Topi Pakistan Faculty of Information Technology Beijing University of Technology Beijing P. R. China Department of Computer Engineering College of Information Technology University of Bahrain Bahrain School of Engineering Edith Cowan University Perth WA Australia

Internet of Things (IoT) is a promising technology that attains significant consideration in diverse industrial areas, i.e., agriculture, engineering, logistics, trading, ecological examining, security surveillance, energy, and healthcare. IoT gains much more attention with the rapid advancement of wireless communication and sensor networks as millions of intelligent devices get involved in IoT. These intelligent devices' raw data must be captured and processed to support decision-making. However, IoT applications trust the central server for information storage, processing, and mediators for wireless transmission. Consequently, it can leak the information and lead to high costs and delays. Hence, data security is the leading interest for the IoT. Blockchain technology can be deployed to overcome the security and effectiveness of the gigantic data in IoT. Blockchain is studied as a key to permitting storing, processing and sharing of data in an efficient, secure manner. In addition, reinforcement learning can convene the high data rate requirements. It will help us to optimize the performance of the blockchain-enabled IoT framework.

关键词： Wireless communication Resistance Performance evaluation Wireless sensor networks Data security Surveillance Reinforcement learning

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A Lightweight Deep Learning Network for Sensor-based Human Activity Recognition using IMU sensors of a Low-Power Wearable Device 25

A Lightweight Deep Learning Network for Sensor-based Human A...

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25th International computer Science and engineering Conference, ICSEC 2021

作者： Jantawong, Ponnipa Hnoohom, Narit Jitpattanakul, Anuchit Mekruksavanich, Sakorn School of Information and Communication Technology University of Phayao Department of Computer Engineering Phayao Thailand Mahidol University Image Information and Intelligence Laboratory Faculty of Engineering Department of Computer Engineering Nakorn Pathom Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Bangkok Thailand

ISBN: (纸本)9781665411974

Human Activity Recognition (HAR) is an intriguing approach to healthcare monitoring that necessitates the ongoing utilization of wearable sensors to capture everyday activities. The most advanced studies using wearable devices have used a cloud computing paradigm that categorized data at remote systems. This method has drawbacks in terms of energy consumption, latency, and privacy. As a result, we adhere to a low-power computing structure in which wearable device solutions achieve an acceptable level of performance while being energy and memory-efficient. This study proposes a lightweight deep learning model termed a gate recurrent unit (GRU) network for energy-efficient HAR appropriate for low-power wearable devices. The introduced GRU network is evaluated against a benchmark dataset named the w-HAR dataset, including essential deep learning networks. The proposed GRU surpasses baseline deep learning networks in terms of overall accuracy, with a score of 95.160%. © 2021 IEEE.

关键词： Energy efficiency

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Real Time Detection of Object Blob Localization Application using 1-D Connected Pixel and Windowing Method on FPGA 5

Real Time Detection of Object Blob Localization Application ...

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5th International Conference on Electronic Design, ICED 2020

作者： Lam, CheeYuen Ehkan, Phaklen Raof, Rafikha Aliana A. Jungjit, Suwimol Research Cluster School of Computer and Communication Engineering Universiti Malaysia Perlis Perlis Arau Malaysia Department of Computer and Information Technology Faculty of Science Thaksin University Phatthalung Thailand

Blob detection and localization is a common process used in the machine vision. Current existing blob detection method is using 2-dimensional kernel matrix which is higher in time consumption and also memory space. This study has proposed a dedicated digital architecture consist of two modules to detect binary image blob using only 1-dimensional image pixel. First module is used to detect connected pixel in a row of pixel, and second module is used to perform windowing to justify blob location. This study has been successfully implemented and tested on Altera DE2 FPGA board. The proposed architecture only takes 24 clock cycles to deliver blob location and related features. The tested architecture only utilizes 1597 logic element, or 4.81% of the FPGA total resources. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Field programmable gate arrays (FPGA)

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Highly-Accurate Robot Calibration Based on Plane Constraint via Integrating Square-Root Cubature Kalman filter and Levenberg-Marquardt Algorithm 19

Highly-Accurate Robot Calibration Based on Plane Constraint ...

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19th IEEE International Conference on Networking, Sensing and Control, ICNSC 2022

作者： Chen, Tinghui Li, Shuai Wu, Hao Chongqing University of Posts and Telecommunications Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing School University of Chinese Academy of Sciences School of Computer Science and Technology Chongqing China Swansea University Faculty of Science and Engineering Swansea United Kingdom Zienkiewicz Centre for Computational Engineering Swansea United Kingdom College of Computer and Information Science Southwest University Chongqing China

ISBN: (纸本)9781665472432

In the field of modern industrial manufacturing, industrial robots are indispensable intelligent automatic mechanical equipment for advanced industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of the manufacturing industry. Calibrating the kinematic parameters of the robot is an effective way to address it. However, the main measuring equipment such as laser trackers and coordinate measuring machines are expensive and need special personnel to operate. Additionally, in the measurement process, due to the influence of extensive environmental factors, measurement noises are generated affecting the calibration accuracy of the robot. Based on these, we have done the following work: a) developing a robot calibration method based on plane constraint to simplify measurement steps;b) employing square-root culture Kalman filter (SCKF) algorithm for reducing the influence of measurement noises;c) proposing a novel algorithm for identifying kinematic parameters based on SCKF algorithm and Levenberg-Marquardt (LM) algorithm to achieve the high calibration accuracy;d) adopting the dial indicator as the measuring equipment for slashing costs. Enough experiments verify the effectiveness of the proposed calibration algorithm and experimental platform. © 2022 IEEE.

关键词： Industrial robots

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