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IEEE 99th Vehicular Technology conference (VTC-Spring)

作者： Zhang, Junying Du, Qinghe Ren, Yijing Zhang, Shijiao Zheng, Hancong Wei, Xueyong Qi, Yonghong Zhang, Yuhao Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian 710049 Peoples R China Kings Coll London Dept Engn London WC2R 2LS England Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Peoples R China Shaanxi Smart Networks & Ubiquitous Access Res Ct Xian 710049 Peoples R China Natl Simulat Educ Ctr Commun & Informat Syst Xian 710049 Peoples R China

ISBN: (纸本)9798350387414

With the emergence of the sixth generation (6G) era, ubiquitous sensing and machine intelligence have emerged as the primary motivation for the development of large-scale Internet of Things (IoT) systems. However, the limited communication capabilities of IoT devices are often constrained by costs and further inhibit their full potential. Nowadays sensor technologies are rapidly evolving, offering improved accuracy and update rates for environmental perception. Considering this, the challenge faced by 6G IoT lies in the increasing data payload from sensing and the constrained communication capacity. To this end, lite communication solutions for IoT are investigated in this paper. By integrating task-oriented communication concepts with sensing objectives, we extract and represent semantic information from sensor nodes. Subsequently, this information is transmitted to edge nodes via wireless transmission for analysis and processing of sensory data. This approach effectively reduces redundant data transmission, thus achieving lite communication in IoT. Based on these principles, a lite edge task-oriented communication system architecture tailored for IoT applications is proposed. Specifically, we implement and evaluate the IoT communication module and the edge task-oriented module, demonstrating that the proposed system reduces resource consumption by 99% and significantly alleviates the transmission payload of IoT. Through leveraging low-speed IoT transmission protocols and high-precision sensors, our system effectively supports a wide range of sensing tasks.

关键词： Task-oriented communications IoT LoRa Edge semantic

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Wireless-Assisted Automatic Online Spatial Calibration based on 5G TSN for sensor Fusion

Wireless-Assisted Automatic Online Spatial Calibration based...

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2023 IEEE International conference on Signal Processing, Communications and Computing, ICSPCC 2023

作者： Lei, Ming Rahman, Mahib Mathaikutty, Deepak Alvarez, Ignacio Intel Corporation

ISBN: (纸本)9798350316728

In the field of artificial intelligence (AI), sensor fusion [1] is becoming an increasingly important technology for many Internet of things (IoT) applications. For intelligent transportation system (ITS), we propose a wireless-assisted automatic online spatial calibration for sensor fusion. Due to the mobility of traffic objects such as vehicles, it is critical to make sure ground truth (GT) position and corresponding sample positions are measured based on raw data collected by different sensors at the same time. We use 5G time sensitive networking (TSN) to achieve this time alignment. Additionally, we illustrate how to perform automatic miscalibration detection and correction based on correctly grouped GT position and sample positions. There are many advantages of using our solution in practical sensor fusion systems that can significantly improve traffic safety and efficiency. © 2023 IEEE.

关键词： Calibration

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Novel flexible sensors with excellent piezoelectric and optical limiting properties 10

Novel flexible sensors with excellent piezoelectric and opti...

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10th International conference on Mechanical Engineering, Materials, and Automation Technology, MMEAT 2024

作者： Zhang, Mingang Zhang, Lin Xu, Yi Wang, xin Wang, Wenfeng Zhang, Bo Yang, Hao Air Defense and Antimissile School Air Force Engineering University Shaanxi Xi’an710056 China

ISBN: (纸本)9781510682634

The novel 0.6 wt% 3,4-dimethoxy-styrene-3-methylbenzothiazole p-toluene sulfonate (DOBT)−polyvinyl alcohol (PVA) binary composite film based flexible sensor is fabricated in this work, and its piezoelectric and third-order nonlinear optical absorption properties are investigated through using linear motor and femtosecond open-operture Z-scan technique, respectively. Piezoelectric measurements indicate that this sensor exhibits desirable piezoelectric properties with an open-circuit voltage of 1.75 V and a short-circuit current of 57.10 nA under an external compressive force of 10 N at 1 Hz. Z-scan traces reveal when irradiated by a 520 nm laser beam, this sensor with a linear transmittance of 94.0% can exhibit remarkable optical limiting performances. In particular, both the piezoelectric and third-order nonlinear optical limiting responses that observed from this sensor originate from the ionic organic molecule DOBT alone, suggesting a promising application prospect of new DOBT in the fields of piezoelectricity and nonlinear optics. These results together establish an experimental foundation for applications of 0.6 wt% DOBT−PVA binary composite film based flexible sensor in sustainable self-powered and high-energy laser protection systems in the future. © 2024 SPIE.

关键词： Piezoelectricity

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Photoelectric Memristor-Based Machine Vision for Artificial Intelligence applications

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ACS MATERIALS LETTERS 2023年第2期5卷 504-526页

作者： Yang, Chuan Sun, Bai Zhou, Guangdong Guo, Tao Ke, Chuan Chen, Yuanzheng Shao, Jinyou Zhao, Yong Wang, Hongyan Southwest Jiaotong Univ Sch Phys Sci & Technol Key Lab Adv Technol Mat Chengdu 610031 Sichuan Peoples R China Southwest Univ Sch Artificial Intelligence Chongqing 400715 Peoples R China Univ Waterloo Waterloo Inst Nanotechnol Dept Mech & Mechatron Engn Waterloo ON N2L 3G1 Canada Southwest Jiaotong Univ Superconduct & New Energy R&D Ctr Chengdu 610031 Peoples R China Xi An Jiao Tong Univ Frontier Inst Sci & Technol FIST Xian 710049 Shaanxi Peoples R China Fujian Normal Univ Fujian Prov Collaborat Innovat Ctr Adv High Field Fuzhou 350117 Fujian Peoples R China

With the rapid development of next-generation artificial intelligence technology, research on advanced machine vision has received extensive attention. It is well-known that significant progress has been made in artificial vision systems based on light sensors, but the separate light sensor and memory require additional time for information transfer to realize computation due to the limitation of the von Neumann architecture, which delays the computational speed and hinders large-scale integration. In recent years, the emergence of photoelectric memristors has brought new inspiration to the study of machine vision, which is expected to overcome the above problems. Photoelectric memristors can not only respond directly to light stimuli but also perform temporary memory and real-time processing of visual information and sensory data, providing a promising hardware foundation for the development of artificial vision systems. In this review, the background and related theory of photoelectric memristors and machine vision are first introduced. Then, the research progress of photoelectric memristors and machine vision based on them is reviewed. Finally, the existing problems impeding the progress of machine vision based on photoelectric memristors are summarized, and the future development is predicted.

关键词： Memristors

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Malware Detection By Distributed systems with Partial Centralization 12

Malware Detection By Distributed Systems with Partial Centra...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Savenko, Bohdan Kashtalian, Antonina Lysenko, Sergii Savenko, Oleg Khmelnytskyi National University Khmelnytskyi29016 Ukraine

ISBN: (纸本)9798350358056

The paper proposes approach to use new tools for malware detection in corporate networks, which are distributed systems with partial centralization. To make decision about malware presence, the components which includes specified decision-making for the system's center are defined as a decentralized subsystem. To determine the states of the system components, characteristic indicators are proposed, and generalized analytical expressions for their calculation are developed. Such calculations make it possible to assess the state of the components in the system in order to determine its further steps. As a result, the system is the basis for usage of different malware detection methods in combination with the system components as an integral sensor. To test the system, a worm-virus detection method was implemented and experiments were conducted. The results of experimental studies approved the efficiency of the proposed solution. © 2023 IEEE.

关键词： distributed systems malware malware detection network security partial centralization worm-virus

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Imprinted CNTs field emission cathode for electron brushing 4

Imprinted CNTs field emission cathode for electron brushing

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2023 4th International conference on advanced Materials and Intelligent Manufacturing, ICAMIM 2023

作者： Wang, Zhanliang Lin, Zhanpeng Yan, Lei Xu, Zhifeng Liu, Jianlong He, Zhiyuan Jianmucuo, Dongzhi Jiang, Ruirui Gong, Yubin Science and Technology on Low-Light-Level Night Vision Laboratory Xi'an710000 China School of Electronic Science and Engineering University Electronic Science and Technology of China Chengdu610054 China Shenzhen Institute for Advanced Study University Electronic Science and Technology of China Shenzhen518000 China

Microchannel plates (MCPs) are the key components for low-level light night vision systems. Electron brushing is a crucial processing for MCPs manufacturing. In this paper, an imprinted carbon nanotubes (CNTs) field emission cathode is fabricated and tested. And the electron brushing experiment based on this cathode is carried out. The result shows that the imprinted CNTs cathode has some advantages and can be used in electron brushing. This research lays the foundation for massive, low cost and highly efficient electron brushing applications in the future. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Field emission cathodes

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Research on sound recognition algorithm for home environment based on residual neural network 7

Research on sound recognition algorithm for home environment...

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7th International conference on advanced Electronic Materials, Computers, and Software Engineering, AEMCSE 2024

作者： Zhou, Mingde xia, Fei Zhao, xiang School of Electronic Engineering Xidian University Xi'an China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781510681866

This paper proposes a sound recognition algorithm for home environment based on deep learning. This algorithm uses the fusion feature extraction method to fuse the two feature extraction methods GFCC and FBank, and uses the fused feature value as the input of the ResNetSE network. Compared with related research, this method is optimized at the model input layer. By fusing two feature extraction methods, it replaces the traditional MFCC feature extraction method and improves the model's classification accuracy for home environment sounds. Experimental results show that the classification accuracy of the FBank-GFCC ResNetSE model proposed in this paper reached 97.4% on the Urbansound8K public data set. Compared with related work, the accuracy is improved by 6.4%. This shows that the algorithm has better performance in home environment sound classification tasks, and provides a more accurate and reliable solution for applications such as security monitoring in smart home systems. © 2024 SPIE.

关键词： Smart homes

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A Compact and Robust 28nm CMOS Temperature sensor with Machine Learning Assisted Design for DVFS SoC

A Compact and Robust 28nm CMOS Temperature Sensor with Machi...

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2023 IEEE International conference on Integrated Circuits, Technologies and applications, ICTA 2023

作者： Ding, Yizhi Zhi, Haochang Li, Jintao Chen, Zhuo Yang, Kaiyue Shan, Weiwei Southeast University Nanjing China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China

ISBN: (纸本)9798350344288

This work presents a compact and robust CMOS temperature sensor with machine learning (ML) assisted design maximizing these performance trade-offs for dynamic voltage and frequency scaling (DVFS) systems-on-chips (SoC). The gain-bandwidth is enhanced using closed-loop current generation and indirect Miller compensation so that the sensor can be powered by a noisy digital supply. The sensor is fabricated in 28nm CMOS process and occupies 0.0075 mm2 consuming 18.15 μ W at room temperature from a 0.9 V supply. Systematical nonlinearity results in an inaccuracy of 3.1% from 0 °C to 100°C after two-point trim. The sensor achieves a 0.25 K resolution in a 2.44 ms conversion time. The measured supply sensitivity is 7.4 °C/V from 0.8 V to 1.05 V. © 2023 IEEE.

关键词： Machine learning

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Decoupled Unknown-Input Observer for Takagi-Sugeno systems: Application to Three Phase Interleaved Boost Converter 1

Decoupled Unknown-Input Observer for Takagi-Sugeno Systems: ...

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1st International conference on Engineering and advanced Technology, ICEEAT 2023

作者： Hamdi, Wail Hammoudi, Mohamed Yacine Okba, Salah Saadi, Ramzi Mohamed Khider University of Biskra Mse Laboratory Biskra Algeria

ISBN: (纸本)9798350383485

This paper presents the application of a Takagi-Sugeno based Decoupled Unknown-Input Observer for Three-Phase Interleaved Boost Converters for fuel cell applications. Harnessing the potential of a single sensor, the proposed methodology efficiently estimates all the remaining system states and the unknown input. This unique implementation of the Decoupled Unknown-Input Observer in the Interleaved Boost Converters ensures precise state estimation while effectively addressing system nonlinearities. Moreover, an observer based controller is implemented to regulate the DC-bus voltage converter, and its performance is confirmed through simulation test. The proposed work promises to enhance the reliability and cost-effectiveness of power conversion systems. © 2023 IEEE.

关键词： Cost effectiveness

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A Novel Machine Learning Strategy for Anomaly Identification Scheme in Wireless sensor Networks Using Supervised Training Principles 5

A Novel Machine Learning Strategy for Anomaly Identification...

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5th International conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Shifani, S. Agnes Mary, A. Antony Metilda, M.I. Mary Rajkumar, G. Vinoth Sutha, M.S. Maheshwari, S. Saveetha University Chennai

ISBN: (纸本)9798350379945

Anomaly detection in Wireless sensor Networks (WSN s) is critical for maintaining the integrity and reliability of various monitoring systems, especially in agricultural settings. The core of this study is the development of a hybrid anomaly detection model, SVM-RFNet, which integrates Support Vector Machines (SVM), Random Forests (RF), and Neural Networks (NN). By applying noise reduction techniques, such as smoothing algorithms, the data quality is significantly enhanced, resulting in cleaner and more stable datasets. Feature engineering, including temporal trend analysis and Principal Component Analysis (PCA), further refines the dataset by extracting and selecting the most informative features. This model combines the strengths of each method, leveraging SVM's robustness in high-dimensional data, RF's ensemble learning capabilities, and NN's ability to learn complex patterns. The SVM-RFNet model achieved an impressive accuracy of 96%, demonstrating its efficacy in real-time anomaly detection. The paper concludes with a discussion on future research directions, including the integration of advanced deep learning techniques and the development of self-healing networks, which promise to further enhance the capabilities and applications of WSN s in various domains. © 2024 IEEE.

关键词： Noise abatement

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